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Arts and the Perceived Quality of Life in British
Columbia
Alex C. Michalos ÆP. Maurine Kahlke
Accepted: 23 March 2009 / Published online: 14 April 2009
Springer Science+Business Media B.V. 2009
Abstract The aims of this investigation were (1) to measure the impact of arts-related
activities on the perceived quality of life of a representative sample of British Columbians
aged 18 years or more in the spring of 2007, and (2) to compare the findings of this study
with those of a sample of 1,027 adults drawn from five B.C. communities (Comox Valley,
Kamloops, Nanaimo, Port Moody and Prince George) in the fall of 2006. Seven hundred
and eight British Columbians responded to a mailed out questionnaire, and the working
data set was weighted by age and education to match the 2006 census statistics for the
province, yielding a fairly representative sample. Speaking quite generally, about 62.0% of
the results for the two samples are very similar. In particular, in both surveys we found that
(a) among arts-related activities in which people participate relatively infrequently (i.e.,
participation is counted in times per year rather than in hours per week), live theatre is
supreme in the strength of its positive correlation with respondents’ perceived quality of
life measured in 7 different ways, and (b) compared to 4 demographic variables (age,
education, household income and body mass index), household income had the highest
average, positive correlation with 7 different measures of respondents’ overall life
assessments, namely, self-assessed general health, satisfaction with life as a whole (single
item), happiness, satisfaction with the quality of life, satisfaction with life as a whole
(5-item index), contentment with life (5-item index) and subjective wellbeing (4-item
index). Different results were found in the province-wide versus the five-communities
survey for the following, among other things, (a) compared to all 7 life assessment mea-
sures, for the province, satisfaction with the quality of life and happiness had the largest
number of significant correlations with arts-related activities measured in hours per week
engaged, while for the five communities, the single measure of satisfaction with the quality
of life had the largest number of significant correlations, and (b) For the province,
A. C. Michalos (&)
University of Northern British Columbia, 3333 University Way, Prince George, BC V2N 4Z9, Canada
e-mail: michalos@unbc.ca
P. M. Kahlke
Institute for Social Research and Evaluation (ISRE), University of Northern British Columbia,
3333 University Way, Prince George, BC V2N 4Z9, Canada
e-mail: hatchp@unbc.ca
123
Soc Indic Res (2010) 96:1–39
DOI 10.1007/s11205-009-9466-1
compared to all 7 life assessment measures, satisfaction with the quality of life had the
largest number of significant correlations with arts-related activities measured in times per
year engaged; for the five communities, compared to all 7 life assessment measures, self-
assessed general health had the largest number of significant correlations with arts-related
activities measured in times per year engaged.
Keywords Quality of life Happiness Arts British Columbia
1 Introduction
In Michalos and Kahlke (2008) we reported the results of a 2006 survey of 1,027 adults in five
communities of British Columbia (Comox Valley, Kamloops, Nanaimo, Port Moody and
Prince George). The aim of that survey was to measure the impact of arts-related activities on
the perceived quality of respondents’ lives. The sample was not drawn in any way that it
could be regarded as representative of the whole provincial population. However, our plan
was to undertake an independent survey in 2007 that would be representative of the whole
province. This paper is a report of the results of that province-wide survey. Specifically, then,
the aims of this investigation are (1) to measure the impact of arts-related activities on the
perceived quality of life of a representative sample of British Columbians aged 18 years or
more, and (2) to compare the findings of this study with those of the earlier study.
As in Michalos (2005b) and Michalos and Kahlke (2008), the term ‘arts’ is used here in
a very broad sense to include such things as music, dance, theatre, painting, sculpture,
pottery, literature (novels, short stories, poetry), photography, quilting, gardening, flower
arranging, textile and fabric art. Although we regard ‘culture’ as a term with a broader
connotation than ‘arts’ and many people seem to treat the two terms as synonyms, such
distinctions should not create any confusion here because we will give a complete list of
everything we consider to be an arts-related activity for the purposes of this study. Again
following the strategy of the two earlier studies, we are not attempting any distinction
between high/fine and low/popular art or culture.
The structure and analyses in this essay follow closely those of Michalos and Kahlke
(2008). In the next Sect. 2we describe our sampling technique and questionnaire, and in
the section after that 3we summarize the characteristics of the sample. The descriptive
statistics resulting from the substantive items in the questionnaire are reviewed in Sect. 4.
In Sect. 5the results of a variety of bivariate analyses are presented, and variables shown to
have statistically significant bivariate associations are used in multivariate analyses in Sect.
6. The concluding Sect. 7provides an overview of our results compared to results from the
earlier study.
2 Sampling Technique and Questionnaire
The 13-page questionnaire used in the survey undertaken for this investigation was a
revised version of one used for the five-community survey described in Michalos and
Kahlke (2008). In May 2007, 5,000 questionnaires were mailed out to a random sample of
households across the whole province of British Columbia. The first three pages of the
questionnaire listed 66 activities that are related in one way or another to the arts, e.g.,
listening to music, teaching painting or drawing, singing in a group, attending live theatre
2 A. C. Michalos, P. M. Kahlke
123
performances. Because people participate in different artistic activities in very different
time periods, from daily (e.g., listening to music) to a few times per year (e.g., attending
live theatre performances), to properly estimate the amount of time committed to such
activities, two different questions were included. For activities involving frequent partic-
ipation, respondents were asked to estimate the average amount of time per week that they
spent on them, in hours. If they never engaged in some particular activity, they were asked
to write 0 for hours per week. For activities involving infrequent participation, respondents
were asked to estimate the number of times per year that they participated in them. If they
never engaged in some particular activity, they were asked to write 0 for times per year.
For those activities in which they participated, they were asked to rate the average level of
satisfaction obtained on a 7-point scale running from 1 =very dissatisfied, 2 or
3=dissatisfied, 4 =even balance of satisfaction and dissatisfaction, 5 or 6 =satisfied, to
7=very satisfied. The Appendix attached to this paper has a complete list of all the
activities sorted and ordered by (1) the numbers of people participating in each, (2) the
average number of hours per week people engaged in each and (3) the average number of
times per year that people engaged in each. Copies of the questionnaire and detailed
responses to all items are available from the corresponding author on request.
Following the frequency-of-participation items, there was a page of questions designed
to get more information about the arts-related activity (out of the 66) that respondents
perceived as ‘‘most important’’. For examples, there were questions about levels of sat-
isfaction with their access to the activity, with the price of engagement and with the usual
venue, and questions about where they first learned about the activity, e.g., in school,
watching television, listening to a friend, and how old they were at the time.
The next two pages listed 45 statements culled from the literature describing people’s
beliefs and feelings about the arts, usually phrased in personal terms, e.g., My artistic
activities help me preserve my cultural heritage, I engage in artistic activities to express my
spirituality, I enjoy art for its own sake. Sometimes the phrasing was impersonal, e.g.,
Artistic activity strengthens a community, Good art needs no justification beyond itself.
Respondents were given a 5-point Likert scale and asked to indicate for each item their
level of agreement or disagreement, with strongly disagree =1 and strongly agree =5.
There were then two pages of standard questions about respondents’ health and quality
of life. These included questions about life as a whole and about specific domains and
aspects of life, e.g., family relations, friendships, sense of meaning in life. Seven overall
assessments of life were used as dependent variables in this study: (1) self-reported general
health using a 5-point scale from poor to excellent, (2) satisfaction with life as a whole
using a 7-point scale from very dissatisfied to very satisfied, (3) satisfaction with the
overall quality of life using a 7-point scale from very dissatisfied to very satisfied, (4)
happiness with life as a whole using a 7-point scale from very unhappy to very happy, (5)
satisfaction with life as a whole using a 5-item index drawn from Diener et al. (1985), (6)
contentment with life using a 5-item index drawn from Lavallee et al. (2007) and (7)
subjective wellbeing using a 4-item index (Michalos et al. 2005). All measures of satis-
faction with particular domains or aspects of life were formatted as 7-point scales running
from very dissatisfied to very satisfied and these measures have been used around the world
for over 30 years (Michalos 2005a).
Following these standard questions, there were two pages of questions designed to test
some of the basic hypotheses of Multiple Discrepancies Theory (MDT, Michalos 1985),
e.g., Considering your life as a whole, how does it measure up to your general aspirations
or what you want out of life?, How does it measure up to the best in your previous
Arts and the Perceived Quality of Life in British Columbia 3
123
experience? This is only the second survey allowing some testing of MDT in the context of
a wide variety of information about arts-related activities and the perceived quality of life.
Finally, there were 2 pages of demographic questions about, e.g., age, sex, marital
status, income and education.
3 Sample Characteristics
A total of 708 (14.2%) useable questionnaires were returned, which form the working
data-set for the survey. Table 1summarizes the main features of the respondent sample.
Table 1 Sample demographics, unweighted and weighted numbers and % and census (Statistics Canada,
2006 Census Data) values, numbers and %
Characteristic Unweighted Weighted Census values
N%N%N%
Gender
Female 455 65.7 457 65.9 1,745,320 51.4
Male 238 34.3 236 34.1 1,649,585 48.6
Total 693 100.0 693 100.0 3,394,905 100.0
Age
20–34 86 12.4 167 24.2 762,435 24.4
35–44 140 20.3 137 19.9 622,615 19.9
45–54 165 23.9 146 21.1 661,485 21.2
55–64 167 24.2 113 16.4 502,645 16.2
65 and over 133 19.2 127 18.4 572,420 18.3
Total 691 100.0 690 100.0 3,121,600 100.0
Education—highest level
Secondary—incomplete 32 4.7 110 16.0 502,270 16.1
Secondary—complete 165 24.0 189 27.5 858,115 27.5
Diploma, certificate, etc. 165 24.0 205 29.7 924,820 29.6
Some university 100 14.5 40 5.8 182,695 5.9
University degree 226 32.8 144 21.0 653,700 20.9
Total 688 100.0 688 100.0 3,121,600 100.0
Employment status
Unemployed 11 1.6 11 1.6 115,000 3.7
Employed 416 60.4 408 59.6 1,973,335 63.2
Not in the labour force 262 38.0 266 38.8 1,033,285 33.1
Total 689 100.0 685 100.0 3,121,620 100.0
Marital status
Now married 406 58.2 395 56.6 1,728,875 54.7
Live-in partner 72 10.3 70 10.0 276,130 8.8
Single—never married 72 10.3 95 13.6 653,715 20.7
Divorced 73 10.5 68 9.8 212,535 6.7
Separated 19 2.7 20 2.9 92,705 2.9
Widowed 56 8.0 50 7.1 196,365 6.2
Total 698 100.0 698 100.0 3,160,325 100.0
4 A. C. Michalos, P. M. Kahlke
123
The first substantive column of the table lists statistics for the unweighted sample, the
second lists those statistics weighted by age and education according to the census of 2006
and the final column lists the 2006 census values for comparative purposes. All of our
analyses are based on the weighted sample.
For the weighted sample, of those respondents who revealed their gender (N=693),
nearly two-thirds (65.9%) were female. Of 690 respondents answering the age question,
44.1% were aged 20–44 and 34.8% were 55 or older, ranging from 18 to 96. Twenty-one
percent of 688 respondents held a university degree and another 29.7% held a diploma or
certificate from a trade, technical, business or community college. Sixty percent of 685
respondents answering the question were employed full-time and 56.6% of 698 respon-
dents were married, with another 10.0% having a live-in partner.
Comparing the figures for the weighted sample with those of the 2006 census, one finds
that the age and education values are practically the same, the weighted sample has 3
percentage points fewer of employed people, 2 percentage points more of married people
and 15 percentage points more of females than the census. Since some studies have found
women to be generally more supportive than men of the arts (Decima 2002, p. 50,
DiMaggio and Pettitt 1999, p. 34), the over-representation of women in our sample may
create a bias in favour of arts-related activities. In fact, split-file analyses (not shown here)
by gender revealed very few differences. If the weighted sample has a bias in favour of
arts-related activities, it is a bias shared fairly equally among respondents regardless of
their gender, i.e., it is a bias resulting from self-selection of respondents. Gender had no
significant impact on any dependent variables in our multiple regression analyses (Sect. 6).
In any event, with the exception of gender, our weighted sample is fairly representative of
the total population of British Columbia.
4 Descriptive Statistics
Table 2lists the top 10 arts-related activities by numbers and percent of participants, with
average hours per week participation and mean levels of satisfaction. The activity with the
highest percentage of participants was listening to music, followed by reading novels, short
stories, plays or poetry. Eighty-four percent (593) reported listening to music an average of
14.0 h per week with a mean level of satisfaction of 6.0. Fifty-eight percent (412) reported
reading novels, etc. an average of 7.4 h per week with a mean level of satisfaction of 6.1.
The third and fourth activities with the highest percentages of participants were watching
Table 2 Top 10 arts-related
activities by number and percent
of participants, with average
number of hours per week par-
ticipation and mean levels of
satisfaction
Activities N% Hours per week Mean sat.
Listening to music 593 83.8 14.0 6.0
Reading novels, etc. 412 58.2 7.4 6.1
Watching films, dvd 293 41.4 5.4 5.6
Singing alone 260 36.7 4.3 5.7
Reading to others 216 30.5 3.5 6.0
Telling stories 141 19.9 3.0 5.9
Gourmet cooking 124 17.5 4.6 6.2
Painting or drawing 120 17.0 5.0 5.9
Singing in a group 100 14.1 2.8 6.1
Watching TV art shows 92 13.0 3.7 5.6
Arts and the Perceived Quality of Life in British Columbia 5
123
films on dvd or video and singing alone, respectively. Forty-one percent (293) of
respondents reported watching films on dvd or video on average 5.4 h per week with a
mean level of satisfaction of 5.6. Thirty-seven percent (260) of respondents reported
singing alone on average 4.3 h per week with a mean level of satisfaction of 5.7. The
activity with the fifth highest percentage of participants was reading to others. Thirty-one
percent (216) reported reading to others an average of 3.5 h per week with a mean level of
satisfaction of 6.0. Comparing the figures in the first five rows of Table 2with their
counterparts in Exhibit 2 of Michalos and Kahlke (2008), one finds the same activities
ordered in the same way, practically the same average levels of satisfaction, and a bit more
disparity among percentages and hours per week of participation.
Table 3lists the top 10 arts-related activities by numbers and percent of participants, with
average times per year participation and mean levels of satisfaction. The activity with the
highest percentage of participants was going to films (cinema, movie theatres). Fifty-eight
percent (409) reported going to films an average of 6.2 times per year with a mean level of
satisfaction of 5.6. The activity with the second highest percentage of participants was going
to concerts. Fifty-four percent (384) reported going to concerts an average of 3.5 times per
year, with a mean level of satisfaction of 6.0. The activity with the third highest percentage of
participants was attending community festivals. Fifty percent (353) of respondents reported
attending community festivals an average of 2.9 times per year, with a mean level of
satisfaction of 5.6. The activities with the fourth and fifth highest percentages of participants
were going to historic, heritage sites and going to art museums and galleries, and the figures
were similar. Forty-nine percent (348) reported going to historic, heritage sites an average of
3.0 times per year, with a mean level of satisfaction of 5.9, while 49% (345) reported going to
art museums and galleries an average of 3.4 times per year, with a mean level of satisfaction
of 5.7. Comparing the figures in the first five rows of Table 3with their counterparts in
Exhibit 3 of Michalos and Kahlke (2008), one again finds the same activities ordered in the
same way, practically the same average levels of satisfaction, and a bit more disparity among
percentages and times per year of participation.
Table 4lists the percent of respondents indicating the first thing they think of when they
hear the word ‘arts’ or the phrase ‘artistic activity’ and respondents’ most important arts-
related activity, with mean levels of satisfaction with nine aspects of that activity. The most
frequently mentioned activity that respondents think of when they hear the word ‘arts’ or
the phrase ‘artistic activity’ is painting and/or drawing. Thirty-eight percent of the sample
gave that response. The most frequently mentioned ‘‘most important’’ arts-related activity
Table 3 Top 10 arts-related
activities by number and percent
of participants, with average
number of times per year partic-
ipation and mean levels of
satisfaction
Activities N% Times
per year
Mean
sat.
Go to movies 409 57.7 6.2 5.6
Go to concerts 384 54.2 3.5 6.0
Go to community festivals 353 49.9 2.9 5.6
Go to historic sites 348 49.2 3.0 5.9
Go to art museums 345 48.7 3.4 5.7
Go to other museums 295 41.6 2.3 5.7
Go to public library 295 41.7 8.2 5.6
Go to amateur theatre 264 37.3 2.4 5.8
Go to prof. theatre 254 35.8 2.7 6.2
Decorating a home 212 29.9 5.9 5.8
6 A. C. Michalos, P. M. Kahlke
123
is music in some form. Thirty-six percent gave that response. The most frequently men-
tioned place where respondents first learned about their most important arts-related activity
is in school. Fifty-five percent gave that response. The mean age at which respondents first
learned about their most important arts-related activity was 12.0 years. Mean satisfaction
levels reported for respondents’ access to information about their most important arts-related
activity (5.3), access to the activity itself (5.4), access to the place where the activity occurs
(5.0) and about the place itself (5.2) were all on the positive side of the 7-point satisfaction
scale. For the remaining five items in the list, three items had mean satisfaction levels in the
middle range and two were on the negative side. Mean satisfaction levels reported for the
price ($) paid for participating in respondents’ most important arts-related activity, for city
government support and support from other sources for the activity were 4.8, 4.1 and 4.4,
respectively. For the amount of provincial government support and federal government
support, the mean satisfaction levels were 3.8 and 3.5, respectively. Comparing the items in
Table 4with their counterparts in Exhibit 4 of Michalos and Kahlke (2008), one again finds
the same two activities ordered in the same way, the same age and place of first encounter,
and practically the same average levels of satisfaction for all items.
Twenty-three of the 45 statements in our questionnaire about beliefs and feelings about
arts-related activities were used to construct four indexes of beliefs and feelings that might
motivate people to engage in arts-related activities. Since correlation coefficients cannot
identify the direction of causality between significantly related variables, it is possible that
significant correlations arise because the experience with arts-related activities leads to
certain beliefs and feelings about the activities. Most likely, the causal arrows run in both
directions although we are using the general label of ‘motivational indexes’ for the four.
Table 5lists each of the four indexes by name, gives the statements included in each, the
percent of respondents agreeing or strongly agreeing with each statement, the item-total
correlation of each statement with the index and Cronbach’s Alpha Coefficient of Reli-
ability. Each index is formed by simply summing the values of the variables included in it.
Besides the four arts-related indexes, Table 5also lists the same information for three
overall life assessment indexes.
Table 4 Percent of respondents
indicating first thoughts about the
meaning of ‘arts’ or ‘artistic
activity’, respondents’ most
important arts-related activity,
place of and age at first encounter
with the activity, and mean levels
of satisfaction with aspects of
that activity
Item Activity, place,
age, % and sat
First thoughts % Painting, drawing 37.9%
Most important % Music 35.8%
Place where first learned about it % School 55.4%
Mean age when first learned about it 12 years
Mean level of satisfaction with
Access to activity itself (N) 5.4 (599)
Access to information re activity (N) 5.3 (616)
Place where activity occurs (N) 5.2 (463)
Access to the activity facility (N) 5.0 (558)
Price ($) for participating (N) 4.8 (479)
City government support for activity (N) 4.1 (501)
Provincial government support (N) 3.8 (481)
Federal government support (N) 3.5 (474)
Other support for the activity (N) 4.4 (455)
Arts and the Perceived Quality of Life in British Columbia 7
123
Table 5 Indexes of beliefs and feelings that might motivate arts-related activity, whole group, satisfaction
with life scale (SWLS), contentment with life assessment scale (CLAS) and subjective wellbeing (SWB)
% Agreeing or
strongly agreeing
Item-total
correlation
a. Index of arts as self-health enhancers, N = 648, a= .87
a
Description: My artistic activities…
Have a positive effect on my life 90.0 .58
Help me to relax 89.8 .70
Help relieve stress 86.0 .72
Contribute to my emotional wellbeing 88.0 .80
Help me to stay healthy 66.8 .55
Contribute to my overall wellbeing 78.8 .70
b. Index of arts as self-developing activities, N = 642, a= .86
b
Description: My artistic activities…
Give me self-confidence 76.1 .64
Help me to learn about myself 73.8 .65
Help me to reveal my thoughts, feelings or physical skills
to others
72.3 .64
Contribute to my self-esteem 74.5 .71
Help me develop my social skills 59.9 .53
Help me express my personal identity 67.4 .69
c. Index of arts as community builders, N = 637, a= .82
c
Item
My artistic activities help me to learn about other people 74.6 .55
My artistic activities help me to accept differences among people 71.4 .55
My artistic activities help me feel connected to this community 49.0 .53
Artists help build community solidarity 70.2 .59
Artistic activity strengthens a community 77.7 .61
Artistic activity in a community increases its social capital 62.9 .62
d. Index of arts and arts-related activities as ends in themselves, N = 639, a= .71
d
Item
The appreciation of art is an art-lover’s reward 66.2 .39
Good art needs no justification beyond itself 72.5 .51
I enjoy art for its own sake 88.3 .64
Without art, life would be very dull 84.1 .42
I engage in artistic activities for the sake of the activities
themselves
68.2 .38
e. Satisfaction with life scale (SWLS), N = 667, a= .90
e
Item
In most ways my life is close to my ideal 35.3 .78
The conditions of my life are excellent 42.3 .79
I am satisfied with my life 49.1 .83
So far I have gotten the important things I want out of life 52.6 .78
If I could live my life over, I would change nothing 34.5 .60
8 A. C. Michalos, P. M. Kahlke
123
Table 5a describes the Index of Arts as Self-Health Enhancers, which has six items and
an Alpha Coefficient of a=0.87. A good representative item is ‘My artistic activities
contribute to my emotional wellbeing’, which has an item-total correlation of r=0.80.
Eighty-eight percent of respondents agreed or strongly agreed with this statement.
Table 5b describes the Index of Arts as Self-Developing Activities, which has six items
and an a=0.86. A good representative item is ‘My artistic activities contribute to my self-
esteem’, which has an item-total correlation of r=0.71. Seventy-five percent of respon-
dents agreed or strongly agreed with this statement.
Table 5c describes the Index of Arts as Community Builders, which has six items and an
a=0.82. A good representative item is ‘Artistic activity strengthens a community’, which
has an item-total correlation of r=0.61. Seventy-eight percent of respondents agreed or
strongly agreed with this statement.
Table 5d describes the Index of Arts and Arts-Related Activities as Ends in Themselves,
which has five items and an a=0.71. A good representative item is ‘I enjoy art for its own
sake’, which has an item-total correlation of r=0.64. Eighty-eight percent of respondents
agreed or strongly agreed with this statement.
Table 5 continued
% Agreeing or
strongly agreeing
Item-total
correlation
f. Contentment with life assessment scale (CLAS), N = 661, a= .87
f
Item
Nothing is currently lacking in my life 32.5 .71
I am living my life to the fullest 32.8 .79
I am very content with my life 48.1 .76
When I examine my life as a whole, I feel that I am not meeting
my aspirations. (Reverse coded)
29.2 .60
I feel dissatisfied because I’m not doing everything that I want to
be doing in my life. (Reverse coded)
28.3 .64
% Very or somewhat sat. Item-total correlation
g. Subjective wellbeing (SWB), N = 675, a= .87
g
Item
How satisfied are you with
Your life as a whole 67.2 .76
Your overall standard of living 64.7 .63
Your overall quality of life 65.8 .80
% Very or somewhat hap. Item-total correlation
How happy would you say you are? 76.4 .68
a
Scale mean =24.6, standard deviation =3.7
b
Scale mean =22.8, standard deviation =4.1
c
Scale mean =22.5, standard deviation =3.6
d
Scale mean =19.7, standard deviation =2.9
e
Scale mean =24.2, standard deviation =6.7
f
Scale mean =22.2, standard deviation =6.6
g
Scale mean =23.0, standard deviation =4.1
Arts and the Perceived Quality of Life in British Columbia 9
123
Table 5e describes the Satisfaction With Life Scale (SWLS) developed by Diener et al.
(1985), which has five items and an a=0.90. A good representative item is ‘I am satisfied
with my life’, which has an item-total correlation of r=0.83. Forty-nine percent of
respondents agreed or strongly agreed with this statement.
Table 5f describes the Contentment with Life Assessment Scale (CLAS) developed by
Lavallee et al. (2007), which has five items and an a=0.87. A good representative item is
‘I am very content with my life’, which has an item-total correlation of r=0.76. Forty-
eight percent of respondents agreed or strongly agreed with this statement.
Table 5g describes the Subjective Wellbeing Index (SWB) developed by Michalos et al.
(2005), which has four items and an a=0.87. It is constructed by summing responses to
four single-item overall life assessment statements concerning one’s satisfaction with life
as a whole, overall standard of living and quality of life, and one’s happiness. Of the four
items in the scale, satisfaction with one’s overall quality of life has the highest item-total
correlation, r=0.80.
Table 6lists the mean levels of domain and overall life satisfaction and happiness.
Generally speaking, with the 7-point satisfaction scale and sample sizes of about 500, dif-
ferences between mean scores of 0.3 or fewer percentage points are not statistically sig-
nificant at the modest level of 0.05%, i.e., 19 times out of 20 one might find such differences
appearing merely by chance. Of the 34 entries in the exhibit, 26 (77%) are on the positive side
of the 7-point satisfaction and happiness scales. Of the 3 entries concerning satisfaction with
government officials, two are the lowest of all the scores in the table. The scores for satis-
faction with federal and provincial officials are the same, 3.6, which means a little dissat-
isfied. Satisfaction with local government officials just reaches the scale mid-point of 4.0.
The mean score for satisfaction with one’s living partner (6.1) is the highest in the table and
the only one in the table above 6.0. Other items with mean scores clustered at the top of the
list include overall happiness (5.9) and satisfaction with life as a whole (5.8). Ignoring the
scores for government officials, the cluster of items at the bottom of the list include satis-
faction with one’s level of social and physical activity (each 4.6), local land pollution and
primary and secondary schools (each 4.8), and amount of free time (4.9). Comparing the
items in Table 6with their counterparts in Exhibit 7 of Michalos and Kahlke (2008), one
again finds striking similarities. In the five-communities study, 75% of 204 entries were on
the positive side of the 7-point scales, with satisfaction with one’s living partner again at the
top (6.2), followed by overall happiness (5.9). The three government items were again at the
bottom, only none reached the mid-point of the scale. Ignoring the scores for government
officials, the cluster of items at the bottom of the list began again with satisfaction with one’s
level of social and physical activity (each 4.7), local land pollution and primary and
secondary schools (each 4.8), and amount of free time and local air quality (each 4.9).
Table 7lists mean scores on respondents’ lives compared to seven different self-
assessment standards. Mean scores reveal that respondents were on the positive side of two
of the seven scales. On average, respondents scored 5.5 on the have-want scale, indicating
that all things considered, their lives provided more than half of what they wanted. They
also thought that their lives provided more than the lives of the average person of their sex
and age in their local area (5.1). This sort of ego-centric bias has been reported by many
researchers, e.g., see Michalos (1991), pp. 123–4. Regarding the other 5 standards, their
scores were only in the middle range, though on the favourable side. Comparing their lives
to what they expect to have in 5 years, they scored 4.8; compared to what they need, they
scored 4.7. For the remaining three comparisons, they scored each the same, 4.6. Com-
paring the items in Table 7with their counterparts in Exhibit 8 of Michalos and Kahlke
10 A. C. Michalos, P. M. Kahlke
123
(2008), one again finds the same two clusters above and below the positive side of the
scale, with the same two items at the top in the same order.
5 Bivariate Relationships
The main task of this section is to review 8 sets of correlational studies to discover
connections among all our survey variables that seem to be interesting in themselves,
suggestive of other likely relationships and potentially useful for the even more interesting
multivariate investigations in the following section.
Table 6 Number of respondents
and mean levels of domain and
life assessment satisfaction and
happiness
Satisfaction with NMean sat.
Your house, apartment, mobile home 694 5.7
Your neighbourhood 693 5.7
Your city, town or rural area 692 5.6
Your family relations, generally 687 5.7
Your living partner 575 6.1
Your job 572 5.4
Your life as a whole 688 5.8
Your friendships 691 5.7
Your physical health 693 5.1
Your psychological health 690 5.4
Your religion or spiritual fulfillment 658 5.2
Your overall standard of living 693 5.6
Your financial security 691 5.0
Your recreation activities 692 5.1
Your level of physical activity 694 4.6
Your level of social activity 689 4.6
Air quality where you live 693 5.2
Drinking water quality where you live 689 5.5
Land pollution where you live 680 4.8
Your sense of meaning in life 690 5.5
Your self-esteem 690 5.5
Your amount of free time 686 4.9
Local primary and secondary schools 613 4.8
Your personal safety near your home 688 5.6
Federal government officials 676 3.6
Provincial government officials 677 3.6
Local government officials 670 4.0
Your overall quality of life 690 5.7
How local people treat you 692 5.7
Your access to health care 687 5.2
What you achieve in life 689 5.3
Your future security 686 5.1
Feeling part of your community 688 5.0
Your overall happiness 690 5.9
Arts and the Perceived Quality of Life in British Columbia 11
123
Table 8lists results of correlating the average number of hours per week engaged in
each of 22 arts-related activities and each activity’s corresponding mean level of
satisfaction (44 items total) with mean scores on our seven overall assessments of life, i.e.,
Table 7 Number of respondents
and mean scores on respondents’
lives compared to diverse
standards
Your life now compared to NMean
What you want from life 687 5.5
What others your age and sex have 692 5.1
What you deserve 684 4.6
What you need 686 4.7
What you expected it would be now 687 4.6
What you expect it to be in 5 years 688 4.8
The best in your previous experience 690 4.6
Table 8 Correlations among average number of hours per week engaged in arts-related activities and levels
of satisfaction with each activity (Act.Sat.) and seven life assessment variables: general health (GH), life
satisfaction (Lsat), happiness (hap), satisfaction with overall quality of life (qolsat), satisfaction with life
scale (SWLS), contentment with life assessment scale (CLAS) and subjective wellbeing (SWB)
Activity Act.Sat. GH Lsat hap qolsat SWLS CLAS SWB NC
Age – ns .11 .09 .09 .16 .19 .15 657
Education – .22 ns ns ns .09 ns .09 654
House/income – ns .09 .11 .16 .15 .12 .19 504
Body Mass Index – -.18 ns ns ns ns ns ns 623
Listening/music .09 ns ns ns ns ns ns ns 566
Reading novels .28 ns ns ns ns ns ns ns 390
Re/nov/sat 1.00 .12 .15 .16 .12 ns ns .15 390
Watch films dvd ns -.14 ns ns ns ns ns ns 281
Singing alone .25 ns -.12 ns ns ns ns ns 248
Singing alone sat 1.00 ns ns .21 .13 ns .19 .14 248
Read to others .26 ns ns ns ns ns ns ns 206
Read others sat 1.00 ns ns .19 ns ns ns ns 206
Telling stories .22 ns ns ns ns -.22 -.18 ns 135
Tell stories sat 1.00 ns ns .21 ns ns ns ns 135
Gourmet cooking .26 ns ns ns ns ns ns ns 115
Gour/cook/sat 1.00 ns ns .36 ns ns ns .19 115
Painting, drawing .25 ns ns ns -.19 ns ns ns 116
Paint/draw/sat 1.00 .18 ns .20 ns ns ns ns 116
Watch TV art ns .33 ns ns .24 ns ns ns 87
Watch TV art/sat 1.00 ns ns ns ns ns -.23 ns 87
Play/music/inst. .27 ns ns -.26 ns ns ns ns 66
Knit/crochet/sat 1.00 ns ns ns .30 ns ns ns 56
Take/kids/arts ns -.39 ns ns ns ns ns ns 51
Take/kids/arts/sat 1.00 ns -.34 ns -.28 ns -.28 -.31 51
Arranging flowers sat 1.00 ns ns .35 .36 .36 .37 .34 44
Make clothes sat 1.00 ns ns ns .39 ns ns .41 35
P\0.05
12 A. C. Michalos, P. M. Kahlke
123
self-reported general health (GH), satisfaction with life as a whole (Lsat), happiness with
life as a whole (Hap), satisfaction with the overall quality of life (qolsat), satisfaction with
life as a whole index (SWLS), contentment with life assessment scale (CLAS), and sub-
jective wellbeing (SWB). As well, the average number of hours per week engaged in each of
the arts-related activities is correlated with each activity’s corresponding mean level of
satisfaction (Act. Sat. in column one of the table). We arbitrarily selected N=30 as a cutoff
figure and examined all zero-order linear associations (Pearson Product Moment Correla-
tions) for activities involving that many respondents or more. The last column in the table
gives the minimum sample size involved in each of the correlations for each row. The first
four rows of the table give the results of correlating 4 demographic variables (age, edu-
cation, household income and Body Mass Index) with the seven overall life assessments.
Our review of the results in Table 8will begin with a discussion of correlations between
each demographic and life assessment variable. Second, we will consider correlations
between the average amount of time invested in each arts-related activity and the average
amount of obtained satisfaction from that investment (results in column under Act.Sat.).
Third, we will examine correlations between time invested and satisfaction obtained for
each arts-related activity on the one hand with each of the seven life assessment variables
on the other, taking each of the latter variables one at a time. Finally, we will give special
attention to some of the variables for time invested and satisfaction obtained that had a
relatively extensive impact on most of the seven life assessment variables.
Twenty-eight (4 97) associations between the demographic and life assessment vari-
ables were measured, and 16 (57.1%) were found to be statistically significant at the
P\0.05 level. (To simplify the discussion, we arbitrarily decided to use a single level of
significance throughout the study.) No demographic variable was significantly correlated
with every life assessment variable, although age and household income were significantly
correlated with 6 of the 7. General Health scores were not correlated with age or household
income, which is unusual and inconsistent with results reported in Michalos and Kahlke
(2008, Exhibit 9). On average, age was correlated with the 6 life assessment variables at
r=0.13, with a high of r=0.19 for the Contentment with Life Assessment Scale (CLAS)
and a low of r=0.09 for happiness (Hap) and satisfaction with the overall quality of life
(qolsat). Education and the Body Mass Index were significantly correlated with three and
one of the seven life assessment variables, respectively. Generally speaking, the 4
demographic variables had weaker associations with the 7 life assessment variables in the
British Columbia sample than in the five-communities sample.
Since we began with 22 arts-related activities that had at least 30 people engaged in
them and each activity produced its own corresponding mean level of satisfaction, there
were 22 92=44 distinct variables to correlate with 7 life assessment variables, giving a
possible 308 significant correlation coefficients. Besides these 308 coefficients, there might
have been 22 more indicating significant associations between each arts-related activity
and its corresponding mean level of satisfaction. The fact that there are only 22 rows of
arts-related activities and/or corresponding satisfaction items in Table 8shows that 22
(50.0%) of the 44 distinct variables had no significant correlations with any of the life
assessment variables and/or a corresponding level of satisfaction variable. Considering
only the 22 variables listed in Table 8, if every measurement had produced a statistically
significant result then there would have been 154 (22 97) cells with numerical values
indicating significant associations between arts-related activities and/or corresponding
levels of satisfaction with each of the 7 life assessment variables plus 8 more values
indicating significant associations between each activity variable and its corresponding
satisfaction variable, rather than the 45 values displayed in the table. Thus, for our sample
Arts and the Perceived Quality of Life in British Columbia 13
123
of 708 respondents, subtracting the 8 values listed in the column headed Act.Sat., there are
only 37 cases out of our original possible 308 (12.0%) of the time-spent on activities
variables and/or variables indicating the satisfaction obtained from those activities that had
significant correlations with our 7 life assessment variables. Considering only the 22
variables listed in Table 8, there are 37 of 154 (24.0%) cases that had significant corre-
lations with the 7 life assessment variables.
Since a person’s engagement in arts-related activities is usually voluntary, one might
expect a statistically significant positive correlation between the time spent engaged in arts-
related activities and the level of satisfaction obtained from the engagement. Although there
are no negative correlations in the Activity Satisfaction (Act.Sat.) column, 3 associations
were not statistically significant. However, because the average number of hours per week
engaged in 11 of the original 22 arts-related activities did not have statistically significant
associations with any other variables, including their corresponding measures of satisfac-
tion, these 11 are not listed in the exhibit. There were, then, a total of 14 (63.6%) activities (3
listed in the table and 11 not listed) with statistically insignificant correlations with their
corresponding mean levels of satisfaction. In all these cases, apparently the average satis-
faction obtained from participation in arts-related activities cannot be the sole or even
primary motivator of engagement. A similar anomaly appears in Table 9regarding arts-
related activities with engagement measured in number of times per year, and it was also
reported in Michalos and Kahlke (2008) for the corresponding tables (Exhibits 9 and 10).
A casual glance at Table 8suggests that there is a great variety of relationships between the
average number of hours per week engaged in arts-related activities and the corresponding
mean levels of satisfaction resulting from that engagement on the one hand, and the seven life
assessment variables on the other. If one tried to measure the impact of arts-related activities
on the perceived quality of people’s lives using only one of these seven scales as one’s
dependent variable, one would inevitably underestimate that impact. Nine (41.0%) of the 22
arts-related activities and/or corresponding mean levels of satisfaction resulting from
engagement in those activities had a significant correlation with only one life assessment
variable, and five (22.7%) more had such a correlation with two life assessment variables.
Close inspection of the seven life assessment columns in Table 8reveals that the
satisfaction with life index (SWLS) had the fewest number (2) of significant associations
with the average number of hours per week engaged in the 22 arts-related activities and/or
the corresponding mean levels of satisfaction resulting from that engagement. Two life
assessment variables had 8 significant correlations with the 22 arts-related activities and/or
the corresponding mean levels of satisfaction resulting from that engagement, namely, the
single item measure of satisfaction with the overall quality of life (qolsat) and the single
item happiness measure (Hap). On average, for the eight significant correlations with
qolsat, r=0.13, and with Hap, r=0.18. Regarding happiness, correlation coefficients ran
from a positive high of r=0.35 for the satisfaction obtained from arranging flowers to a
negative low of r=-0.26 for the average number of hours per week playing music.
Regarding satisfaction with the overall quality of life, correlation coefficients ran from a
positive high of r=0.39 for the satisfaction obtained from making clothes to a negative
low of r=-0.28 for the satisfaction obtained from taking children to arts-related
activities.
While we were prepared to find that the average amount of time invested in some arts-
related activities was negatively associated with one or another life assessment variable (cf.
Michalos and Kahlke 2008, Exhibit 9), we were surprised to find that the average level of
satisfaction obtained from engaging in some arts-related activities could have negative
associations. Nevertheless, Table 8shows that there were five such cases, involving the
14 A. C. Michalos, P. M. Kahlke
123
satisfaction obtained from watching art shows on television and taking children to arts-
related activities. Remarkably, the only statistically significant associations these four arts-
related satisfaction variables had with any overall life assessment variables were negative.
What’s more, neither of the two arts-related satisfaction variables had significant associ-
ations with the average number of hours per week invested in the corresponding arts-
related activities, e.g., there was no significant correlation between the average number of
hours per week spent watching art programs on television and satisfaction obtained from
such activity. So, some respondents spent some time engaged in arts-related activities that
generated immediate satisfaction that had no significant association with the activities
themselves but was significantly and negatively related to some overall life assessment
variables. How can we explain engagement in such activities and the negative impact that
satisfaction from such engagement has on life assessment variables?
One might argue that one of the two arts-related activities is not a case of engaging in
art at all, i.e., driving kids to some kind of artistic event or facility is not engaging in art.
So, for present purposes the negative associations between satisfaction obtained from such
Table 9 Correlations among average number of times per year engaged in arts-related activities and levels
of satisfaction with each activity (Act.Sat.) and life assessment variables: general health (GH), life satis-
faction (Lsat), happiness (hap), satisfaction with overall quality of life (qolsat), satisfaction with life scale
(SWLS), contentment with life assessment scale (CLAS) and subjective wellbeing (SWB)
Activity Act.Sat. GH Lsat hap qolsat SWLS CLAS SWB NC
Go to movies .22 ns ns ns ns ns -.12 ns 390
Go concerts .15 ns ns ns ns ns ns ns 367
Go concert sat 1.00 ns .16 .17 .13 ns ns .17 367
Go his/her site .15 ns ns ns .15 .11 ns .14 333
Go his/her sat 1.00 ns ns ns .14 ns .15 .13 333
Go art museum .10 ns ns ns ns ns ns ns 330
Go art museum sat 1.00 .15 .20 .19 .17 .16 .14 .22 330
Go other museum sat 1.00 .15 .23 .19 .21 .22 .17 .26 284
Go public library .29 ns ns ns ns ns ns ns 283
Go public library sat 1.00 ns .14 ns ns .14 ns ns 283
Go amateur theatre .23 .14 ns ns ns ns ns ns 251
Go amateur theatre sat 1.00 .14 .34 .22 .31 .32 .23 .35 251
Go prof theatre sat 1.00 ns .29 .25 .23 .26 .23 .29 243
Decorating home .14 ns ns ns ns ns ns ns 201
Decorating home sat 1.00 ns .15 .17 ns ns ns ns 201
Go to school plays sat 1.00 ns .22 .23 .17 .22 .18 .24 204
Buy art work .14 ns ns ns ns ns ns ns 198
Buy art work sat 1.00 ns .22 .15 .24 ns .17 .22 198
Des. Garden sat 1.00 ns ns ns .15 ns .20 ns 187
Go dancing .15 ns ns ns ns ns ns ns 173
Go dancing sat 1.00 ns ns ns .18 ns ns ns 173
Wk com. Fes sat 1.00 ns ns .25 ns ns ns ns 90
Give art dona sat 1.00 ns .22 ns ns .32 .29 ns 84
Figure skating .33 ns ns ns ns ns ns ns 35
Figure skating sat 1.00 ns ns .39 ns ns ns ns 35
P\0.05
Arts and the Perceived Quality of Life in British Columbia 15
123
activities and life assessment measures is irrelevant. Unfortunately, this does not address
the problem that some kinds of satisfaction have a negative impact on other kinds of
satisfaction. It is generally assumed, in the bottom-up explanatory model of perceived life
satisfaction for example, that satisfaction from diverse sources and possibly of diverse
kinds are routinely combined to produce satisfaction with life as a whole. While it is easy
to understand how the time invested in driving one’s kids to an art class might have a
negative impact on one’s life satisfaction (although we have no evidence that it did), it is
far from clear why the satisfaction obtained from driving one’s kids to the class should
have a negative impact. Why should feeling good about driving one’s kids to class have a
negative impact on how one feels about one’s life as a whole? Apparently the activity is
some kind of a mixed blessing. One drives the kids to art class feeling pretty good about it
because it makes the kids happy and is the right thing to do. Nevertheless, that pretty good
feeling is not measurably significantly associated with the activity itself but has the
unintended consequence of depressing one’s satisfaction with the overall quality of life.
The actor performs an act somewhat begrudgingly and the modest level of satisfaction
obtained from it takes a heavy negative toll on the actor’s overall life assessment.
There clearly are associations between time invested in activities and satisfaction
obtained from the investment that were too weak to be captured by some of our measuring
instruments, e.g., we have reported satisfaction obtained from arranging flowers and
although it had no significant association with the time invested in the activity, it had
significant correlations with several overall life assessment variables. It is theoretically
possible that the reported satisfaction obtained from arranging flowers is really an effect of
some kind of genetically hard-wired core affect that is somehow (wittingly or unwittingly)
connected to the activity of arranging flowers. Davern et al. (2007) and Cummins et al.
(2007) made an interesting case for such phenomena, although Moum (2007) and Land
(2007) were not persuaded. While there must be some genetic connection to people’s
experiences and feelings, it is far from clear why one’s genes would produce certain effects
with some arts-related activities and not others. In any event, at this point we have no good
genetically-based explanation for the oddities just reported.
Inspection of all the figures in the 22 rows concerning arts-related activities and cor-
responding levels of satisfaction reveals that there are only two cases in which as many as
five significant correlations with life assessment variables appear, namely, for the satis-
faction obtained from reading novels, etc. and the satisfaction obtained from arranging
flowers. On average, for the five significant correlations with the satisfaction obtained from
reading novels, etc., r=0.14, and with the satisfaction obtained from arranging flowers,
r=0.36. While the flower arrangers got a much bigger average boost than the readers of
novels, etc. in their life assessment scores, there may have been as few as only 44 of the
former compared to as few as 390 of the latter. Regarding the satisfaction obtained from
reading novels, etc., correlation coefficients ran from a high of r=0.16 for happiness to a
low of r=0.12 for general health and satisfaction with the overall quality of life.
Regarding the satisfaction obtained from arranging flowers, correlation coefficients ran
from a high of r=0.37 for the contentment with life assessment scale (CLAS) to a low of
r=0.34 for subjective wellbeing.
Considering the relative number of arts-related activities engaged in fairly frequently
and/or their corresponding levels of satisfaction that were significantly correlated with Hap
and/or qolsat, it seems that if one were looking for associations between such activities
and/or their corresponding satisfaction with the perceived quality of life, one’s chances for
finding such associations would be maximized by using either of these two measures and
16 A. C. Michalos, P. M. Kahlke
123
minimized by using either SWLS or Lsat. Still, one’s best strategy would be to use several
dependent variables.
As we found in our earlier study, there was some evidence that producing art was more
highly correlated with immediate satisfaction than consuming art. Of the eight variables
indicating the average number of hours per week engaged in arts-related activities with
significant associations, 5 referred to production (i.e., singing alone, gourmet cooking,
painting and drawing, playing a musical instrument and telling stories) and 3 referred to
consumption (i.e., listening to music, reading novels, etc., and reading to others). On
average, the productive activities correlated at r=0.25 while the consumptive activities
correlated at r=0.21 with the corresponding immediate satisfaction. In the most extreme
case, the average number of hours per week engaged in listening to music had a correlation
of r=0.09 with its corresponding satisfaction, compared to the correlation of r=0.27
between playing a musical instrument and its corresponding satisfaction. Of course, many
more respondents could listen to music (at least 566) than produce it (possibly as few as
66).
Table 9lists results of correlating the average number of times per year engaged in each
of 19 arts-related activities and each activity’s corresponding mean level of satisfaction (38
items total) with mean scores on our 7 overall assessments of life, and correlating the
average number of times per year engaged in each of the 19 activities with each activity’s
corresponding mean level of satisfaction (Act.Sat.). Our cutoff figure for measuring
associations was N=32 simply because the activity with the next lowest number of
participants had only N=8. Our review of the results in this table will follow the pattern
established for Table 8.
Beginning with 19 arts-related activities that had at least 32 respondents engaged in
them and each activity’s corresponding mean level of satisfaction, there were 19 92=38
distinct variables to correlate with 7 life assessment variables, giving a possible 266
significant correlation coefficients. Besides these 266 coefficients, there might have been
19 more indicating significant associations between each arts-related activity and its cor-
responding mean level of satisfaction. The fact that there are only 25 rows of arts-related
activities and/or corresponding satisfaction items in Table 9shows that 13 (34.2%) of the
38 distinct variables had no significant correlations with any of the life assessment vari-
ables and/or a corresponding level of satisfaction variable. Considering only the 25 vari-
ables listed in Table 9, if every measurement had produced a statistically significant result
then there would have been 175 (25 97) cells with numerical values indicating significant
associations between arts-related activities and/or corresponding levels of satisfaction with
each of the 7 life assessment variables plus 10 more values indicating significant associ-
ations between each activity variable in the table and its corresponding satisfaction vari-
able, rather than the 72 values displayed in the table. Thus, for our sample of 708
respondents, subtracting the 10 values listed in the column headed Act.Sat., there are only
62 cases out of our original possible 175 (35.4%) time-spent on activities variables and/or
variables indicating the satisfaction obtained from those activities that had significant
correlations with our 7 life assessment variables. Although this is not a particularly high
percentage, it is larger than that concerning arts-related activities with frequency of par-
ticipation counted in hours per week. What is perhaps even more interesting is the fact that
there is only one negative correlation in Table 9. In our earlier study, we found that all the
time spent on and the satisfaction obtained from the arts-related activities listed in the times
per year table made a positive contribution to one or more of the overall life assessments.
Here we find that only the time invested in going to movies has a negative association with
one overall life assessment index, i.e., for CLAS, r=-0.12.
Arts and the Perceived Quality of Life in British Columbia 17
123
There are 10 out of a possible 19 (52.6%) statistically significant correlations in the
Act.Sat. column, with an average value of r=0.19, ranging from a high of r=0.33 for
the average number of times per year respondents engaged in figure skating (How
Canadian!) to a low of r=0.10 for the average number of times per year respondents went
to art museums. Of course, many more people reported going to art museums (at least 330)
than engaging in figure skating (perhaps as few as 35). There is again (as in Table 8)a
great variety of relationships (i.e., heterogeneity of effects) between the average number of
times per year engaged in the 19 arts-related activities and the corresponding mean levels
of satisfaction resulting from that engagement on the one hand, and the 7 life assessment
variables on the other.
Inspection of the 7 life assessment columns in Table 9reveals that General Health (GH)
had the fewest number of significant associations with the average number of times per
year engaged in the 19 arts-related activities and the corresponding mean levels of satis-
faction resulting from that engagement. Three of the 4 correlations with GH are with
activity satisfaction variables that have significant and positive associations with each of
the 7 life assessment variables. On average, the mean level of satisfaction obtained from
visiting art museums has a correlation of r=0.18 with the 7 life assessment variables,
ranging from a high of r=0.22 for subjective wellbeing (SWB) to a low of r=0.14 for
CLAS. The mean level of satisfaction obtained from visiting other museums has an
average correlation of r=0.20 with the 7 life assessment variables, ranging from a high of
r=0.26 for SWB to a low of r=0.15 for GH. The mean level of satisfaction obtained
from going to amateur theatre performances has an average correlation of r=0.27 with
the 7 life assessment variables, ranging from a high of r=0.35 for SWB to a low of
r=0.14 for GH.
Satisfaction with the overall quality of life (qolsat) had the largest number of significant
and positive associations with the average number of times per year engaged in the 19 arts-
related activities and the corresponding mean levels of satisfaction resulting from that
engagement. The 11 significant correlations in the qolsat column have an average of
r=0.19, with a high of r=0.31 for the satisfaction obtained from going to amateur
theatre performances to a low of r=0.13 for the satisfaction obtained from going to
concerts. In our earlier study, General Health had the largest number of significant and
positive associations with times per year and corresponding satisfaction variables.
Considering the facts that the average level of satisfaction obtained from going to live
amateur, professional and school theatre performances are significantly and positively
correlated with 7, 6 and 6 of the life assessment variables, respectively, such theatre
performances should be given special recognition. As we discovered and emphasized in
our earlier study, among the 19 arts-related activities in which people participate relatively
infrequently (i.e., participation is counted in times per year rather than in hours per week),
live theatre is supreme in the strength of its correlation with respondents’ perceived quality
of life measured in diverse ways. If this is any reflection of the contribution of dramatists to
the quality of human existence for over 2,500 years, they may be justifiably proud of it.
Table 10 lists results of correlating our 7 life assessment variables with 21 domain
satisfaction variables. Three of the domain satisfaction variables are combinations of some
of those listed in Table 6. Values for the health satisfaction variable appearing in Table 10
were obtained by calculating the mean of the scores on the physical and psychological
health satisfaction variables. Similarly, values for the environmental satisfaction variable
appearing in Table 10, were obtained by calculating the mean of the scores on the air,
water and land quality satisfaction variables, and values for the government satisfaction
variable were obtained by calculating the mean of the scores on the federal, provincial and
18 A. C. Michalos, P. M. Kahlke
123
local government officials satisfaction variables. All of the 147 correlations listed in this
table are significant and positive. In the corresponding table of Michalos and Kahlke (2008,
Exhibit 11), all of the correlation coefficients are also positive and significant. Examination
of the mean values of each row in the table reveals that on average for our respondents,
satisfaction with one’s health (mean r=0.60), self-esteem (mean r=0.59) and the sense
of meaning in life (mean r=0.55) have the largest correlations with the 7 life assessment
variables. These were also the top three in our earlier study, with the same order and
similar correlation coefficients, i.e., r=0.64, r=0.57 and r=0.54, respectively.
Smallest correlations on average were for satisfaction with government officials (mean
r=0.20), access to health care (mean r=0.29) and the environment (mean r=0.28).
Table 11 lists the correlations among the 7 life assessment variables, all of which are
significant and positive as expected. On average and as usual, General Health (GH) has the
lowest levels of association with the others, indicating that respondents recognize
important differences between having good health and having a good life, generally
speaking. Because happiness (Hap), satisfaction with life as a whole (Lsat) and satisfaction
with the overall quality of life (qolsat) are constituents of subjective wellbeing (SWB), the
former three variables have on average the highest levels of association with the latter.
Considering the facts that (1) respondents recognize a difference between good health and
a good life, and (2) qolsat had the greatest number of significant correlations with
Table 10 Correlations of domain satisfaction scores with life assessment variables: general health (GH),
life satisfaction (Lsat), happiness (hap), satisfaction with overall quality of life (qolsat), satisfaction with life
scale (SWLS), contentment with life assessment scale (CLAS) and subjective wellbeing (SWB)
Domain sat with GH Lsat hap qolsat SWLS CLAS SWB Mean
Your house, apartment .11 .43 .38 .44 .39 .38 .51 0.38
Neighbourhood .12 .36 .34 .41 .37 .32 .47 0.34
City, town or rural area .11 .34 .28 .38 .33 .30 .40 0.31
Family relations .11 .46 .37 .41 .40 .33 .49 0.37
Living partner .18 .46 .37 .44 .43 .32 .49 0.38
Job .20 .53 .37 .40 .46 .43 .51 0.41
Friendships .25 .59 .47 .53 .43 .43 .60 0.47
Health .63 .66 .51 .62 .56 .53 .68 0.60
Religion/spirit fulfill .26 .43 .34 .44 .43 .40 .47 0.40
Financial security .25 .44 .44 .55 .48 .46 .64 0.47
Recreation activities .39 .49 .45 .60 .46 .43 .61 0.49
Environment .18 .28 .27 .37 .28 .25 .36 0.28
Sense of meaning in life .23 .65 .54 .61 .58 .57 .68 0.55
Self-esteem .29 .66 .63 .63 .61 .63 .71 0.59
Amount of free time ns .35 .32 .40 .32 .33 .39 0.35
Personal safety by home .19 .41 .35 .50 .38 .31 .50 0.38
Government officials .11 .18 .15 .29 .19 .21 .24 0.20
How locals treat you .25 .56 .44 .63 .50 .48 .64 0.50
Access to health care .21 .27 .26 .38 .32 .24 .36 0.29
Future security .25 .50 .51 .62 .54 .54 .67 0.52
Feel part of your comm. .19 .54 .49 .58 .54 .51 .63 0.50
NC553; P\0.05
Arts and the Perceived Quality of Life in British Columbia 19
123
arts-related activities involving infrequent engagement and tied with Hap for having the
greatest number of significant correlations with arts-related activities involving frequent
engagement, it seems fair to say that if one were looking for associations between such
activities and the perceived quality of life and if one could only have a single dependent
variable, then one’s chances for finding such associations would be maximized by using
qolsat as that single variable.
Tables 12 and 13 display results of measuring associations among our four indexes that
might provide motives for people engaging in arts-related activities, might summarize
beliefs and feelings that arise as effects of experiences with arts-related activities or, as
suggested earlier, most likely both. We will need longitudinal studies with panels of
participants in order to properly assess these issues. Our review of these two tables will be
parallel to our reviews of Tables 8and 9, with Table 12 involving engagement in arts-
related activities measured in hours per week and Table 13 involving engagement in arts-
related activities measured in times per year.
Table 12 lists results of correlating the average number of hours per week engaged in
each of 22 arts-related activities and each activity’s corresponding mean level of satis-
faction (44 items total) with mean scores on our four motivational indexes. The fact that
there are only 17 rows of arts-related activities and/or corresponding satisfaction items in
Table 12 shows that 27 (61%) of the 44 distinct variables had no significant correlations
with any of the motivational indexes. For this table, 16 associations between the 4
demographic variables and 4 motivational indexes were also measured, and 10 (62.5%)
were found to be statistically significant at the P\0.05 level. Household income does not
appear in the table because it did not have any significant correlations with the four
motivational indexes. Education and the Body Mass Index were significantly correlated
with each index, positively with an average of r=0.13 for the former and negatively with
an average of r=-0.20 for the latter. Age was negatively correlated with 2 of the 4
indexes, averaging r=-0.10. Thus, for example, believing and/or feeling that engage-
ment in arts-related activities make a positive contribution to one’s health is significantly
negatively correlated with age (r=-0.08) and Body Mass Index (r=-0.22), and pos-
itively correlated with education (r=0.16). So, as respondents’ age and BMI increased,
the strength of their avowal of such beliefs and/or feelings decreased, and as their achieved
level of education increased, the strength of their avowal of such beliefs and/or feelings
increased, and vice versa.
Table 11 Correlations among seven life assessment variables: general health (GH), life satisfaction (Lsat),
happiness (hap), satisfaction with overall quality of life (qolsat), satisfaction with life scale (SWLS),
contentment with life assessment scale (CLAS) and subjective wellbeing (SWB)
Variable GH Lsat hap qolsat SWLS CLAS
GH 1.00
Lsat .38 1.00
Hap .32 .67 1.00
Qolsat .40 .72 .64 1.00
SWLS .40 .68 .68 .66 1.00
CLAS .31 .64 .66 .61 .80 1.00
SWB .41 .87 .83 .88 .76 .72
NC639; P\0.05
20 A. C. Michalos, P. M. Kahlke
123
Considering only the 17 non-demographic variables listed in Table 12, if every mea-
surement had produced a statistically significant result then there would have been 68
(4 917) cells with numerical values, rather than the 30 values displayed in the table. Thus,
only 44% of the time-spent on activities variables and/or variables indicating the satis-
faction obtained from those activities had significant correlations with our 4 motivational
indexes. (There is no comparable figure from the earlier study because the number and
composition of arts-related variables and motivational indexes are different.) Inspection of
the 4 motivational index columns in this table reveals that the Index of Arts as Community
Builders (Comb) had the fewest number of significant associations with the average
number of hours per week engaged in the 17 arts-related activities and the corresponding
mean levels of satisfaction resulting from that engagement. The 5 significant correlations
in the column have an average of r=0.23, with a high of r=0.37 for the satisfaction
obtained from teaching painting or drawing to a low of r=0.15 for the satisfaction
obtained from reading novels, etc. and singing alone. The Index of Arts as Self-Health
Enhancers (Health) had the largest number of significant associations with the average
number of hours per week engaged in the 17 arts-related activities and the corresponding
mean levels of satisfaction resulting from that engagement. The 10 significant correlations
in the Health column have an average of r=0.27, with a high of r=0.37 for the
satisfaction obtained from arranging flowers to a low of r=0.10 for the average number
of hours per week spent listening to music.
Table 12 Correlations among average number of hours per week engaged in arts-related activities and
levels of satisfaction with motivational indexes: index of arts as self-health enhancers (Health), index of arts
as self-developing activities (S-Dev), index of arts as community builders (Comb), index of arts as ends in
themselves (Ends), and demographics
Activity Health S-Dev Comb Ends NC
Age -.08 -.11 ns ns 629
Education .16 .09 .15 .13 628
Body Mass Index -.22 -.21 -.21 -.14 604
Listening to music .10 .13 ns .13 545
Listening to music satisfaction .28 .24 .17 .22 545
Reading novels satisfaction ns .12 .15 ns 380
Singing alone satisfaction .32 .33 .15 .16 249
Reading to others satisfaction .25 ns ns ns 206
Gourmet cooking ns ns ns -.20 117
Gourmet cooking satisfaction .25 ns ns ns 117
Painting or drawing ns ns ns .25 113
Painting or drawing satisfaction .27 .24 ns .20 113
Singing in a group satisfaction .26 ns ns ns 91
Watching TV art satisfaction .24 ns ns ns 84
Playing musical instrument sat. .33 ns .31 ns 64
Arranging flowers ns ns ns .33 43
Arranging flowers satisfaction .37 .40 ns ns 43
Writing novels…etc. sat ns .48 ns ns 30
Making clothes ns ns ns .53 35
Teaching painting/drawing sat ns ns .37 ns 29
P\0.05
Arts and the Perceived Quality of Life in British Columbia 21
123
Two arts-related variables in Table 12 had significant and positive associations with
each of the 4 motivational indexes, and 2 had significant and positive associations with 3 of
the 4. Satisfaction obtained from singing alone had an average correlation of r=0.24 with
the 4 motivational indexes, with a high of r=0.33 for S-Dev and a low of r=0.15 for
Comb. Thus, for example, as respondents’ average levels of satisfaction obtained from
singing alone increased, the strength of their beliefs and/or feelings that arts-related
activities contributed to their health, self-development, community building and were also
enjoyed as ends in themselves increased. Satisfaction obtained from listening to music had
an average correlation of r=0.23 with 4 motivational indexes, with a high of r=0.28 for
Health and a low of r=0.17 for Comb. Satisfaction obtained from painting or drawing
had an average correlation of r=0.24 with 3 of the 4 motivational indexes (missing
Comb), with a high of r=0.27 for Health and a low of r=0.20 for Ends. Average
number of hours per week engaged in listening to music had an average correlation of
r=0.12 with 3 of the 4 motivational indexes (again missing Comb), with a high of
r=0.13 for S-Dev and Ends, and a low of r=0.10 for Health.
Table 13 lists results of correlating the average number of times per year engaged in each
of 19 arts-related activities and each activity’s corresponding mean level of satisfaction with
mean scores on our four motivational indexes (38 items total). If every measurement for
Table 13 Correlations among average number of times per year engaged in arts-related activities and
levels of satisfaction with motivational indexes: index of arts as self-health enhancers (Health), index of arts
as self-developing activities (S-Dev), index of arts as community builders (Comb), index of arts as ends in
themselves (Ends)
Activity Health S-Dev Comb Ends NC
Going to movies ns .14 .13 .12 384
Going to movies satisfaction .11 .10 ns .16 384
Going to concerts .12 .17 .17 .15 358
Going to concerts satisfaction .16 .13 .18 .19 358
Attending community festivals .12 .16 ns ns 330
Attending community festivals sat .16 .19 .20 .12 330
Visiting historic, heritage sites ns .12 ns ns 333
Visiting historic, heritage site sat .15 .15 ns .13 333
Going to art museums, galleries .13 .16 ns ns 324
Go…art museums, galleries sat .23 .22 .26 .20 324
Go…other museums .15 ns ns ns 282
Go…other museums sat .22 .19 .24 .13 282
Visiting public library sat .14 ns ns ns 280
Go…amateur live theatre ns .22 .16 ns 245
Go…amateur live theatre sat ns .13 .26 ns 245
Go…prof. live theatre sat .14 ns ns .16 234
Decorating a home sat .23 .17 ns ns 200
Volunteering in the arts sat ns ns .46 ns 200
Go to school plays satisfaction .15 .16 .27 ns 198
Buying works of art sat .17 ns ns .18 200
Designing a garden sat .23 ns ns ns 188
Making donations to arts sat .22 ns ns ns 82
P\0.05
22 A. C. Michalos, P. M. Kahlke
123
Table 13 had produced a statistically significant result then there would have been 152
(4 938) cells with numerical values, rather than the 52 values displayed in the exhibit.
Thus, for our sample of 708 respondents, 52 of 152 (34.2%) time-spent on activities vari-
ables and/or variables indicating the satisfaction obtained from those activities had signif-
icant correlations with our four motivational indexes. One should notice first that there are no
negative correlations in Table 13. Whether the causal arrows running from the time spent on
the 19 kinds of arts-related activities and the satisfaction obtained from the engagement to
beliefs and/or feelings about the arts are stronger, the same or weaker than the arrows
running in the opposite direction, if there is any influence at all, it is positive.
Inspection of the four motivational index columns in Table 13 reveals that the Indexes
of Arts as Community Builders (Comb) and as Ends in Themselves (Ends) had the fewest
number of significant associations (10) with the average number of times per year engaged
in the 19 arts-related activities and the corresponding mean levels of satisfaction resulting
from that engagement. The Index of Arts as Self-Health Enhancers (Health) had the largest
number of significant associations (17) with the average number of times per year engaged
in the 19 arts-related activities and the corresponding mean levels of satisfaction resulting
from that engagement. The 17 significant correlations in the Health column have an
average of r=0.17, with a high of r=0.23 for the satisfaction obtained from going to art
museums, decorating a home and designing a garden to a low of r=0.11 for the satis-
faction obtained from going to movies.
Five arts-related time-engaged or satisfaction variables had significant correlations with
all four motivational variables, and 4 more of the former had such correlations with 3 of the
latter 4. First among the five, satisfaction obtained from going to art museums had an average
of r=0.23 for the 4 motivational indexes, with a high of r=0.26 for Comb and a low of
r=0.20 for Ends. Satisfaction obtained from going to other kinds of museums ran second,
with an average of r=0.20 for the 4 motivational indexes, a high of r=0.24 for Comb and
a low of r=0.13 for Ends. First among the 3 out of 4 group, satisfaction obtained from
going to school plays had an average of r=0.19 for Health, S-Dev and Comb.
Table 14 lists the correlations among the 4 motivational indexes themselves and
Table 15 lists the correlations among these 4 indexes and our 7 life assessment variables.
The four motivational indexes in Table 14 are fairly strongly related, with the lowest
coefficient at r=0.53 between Ends, S-Dev and Comb. The Index of Arts as Community
Builders was modestly significantly correlated with 6 of the 7 life assessment variables at
r=0.15, with a high of r=0.24 for General Health and a low of r=0.09 for happiness
(Table 15). General Health (GH) was the only life assessment variable significantly
associated with all 4 motivational indexes.
Table 14 Correlations among motivational indexes: Index of Arts as Self-Health Enhancers (Health),
Index of Arts as Self-Developing Activities (S-Dev), Index of Arts as Community Builders (Comb), Index of
Arts as Ends in Themselves (Ends)
Index Health S-Dev Comb
Health 1.00
S-Dev .73 1.00
Comb .57 .65 1.00
Ends .59 .53 .53
NC618; P\0.05
Arts and the Perceived Quality of Life in British Columbia 23
123
6 Multivariate Relationships
Stepwise multiple regression was applied to explain the variation in scores for our 7 overall
life assessment variables, and each of the next 7 tables (16–22) is laid out in the same
format, with three exceptions in which one or two columns were omitted for lack of
significant entries. When all columns are included, the lefthand column lists the names of
the predictors. Then there is a column headed ‘Demog.’ containing the standardized
regression coefficients (Beta values) resulting from regressing a life assessment (depen-
dent) variable on the four demographic (explanatory, predictor or independent) variables.
Standardized regression coefficients have means of zero and standard deviations of one,
making comparisons of their relative influence on dependent variables easy to discern.
Because standardization is sensitive to the particular variance of the variables employed in
any sample, one cannot infer that relationships appearing in one sample must appear in
others. The second column of figures is headed ‘Mot. Index’ and it contains the Beta values
resulting from regressing the same life assessment variable on our four motivational
indexes. The third column of figures is headed ‘Hrs/act.sat.’ and it contains the results of
regressing the same life assessment variable on the set of hours-spent and satisfaction-
obtained variables from Table 8that had statistically significant correlations with that life
assessment variable. The fourth column of figures is headed ‘Times/sat.’ and it contains the
results of regressing the same life assessment variable on the set of times-spent and
satisfaction-obtained variables from Table 9that had statistically significant correlations
with that life assessment variable. The fifth column of figures is headed ‘Domain sat.’ and
it contains the results of regressing the same life assessment variable on the 8 variables
indicating satisfaction obtained from some domain or aspect of life listed in Table 10 that
had the largest correlation coefficients with that life assessment variable. Finally, the sixth
column of figures is headed ‘All Pred’ and it contains the results of regressing the same life
assessment variable on all of the predictors that achieved statistical significance in the
previous five regressions. Because the introduction of any arts-related additional predictors
to the set of significant domain satisfaction predictors drastically reduced the sample size
(N) for the regression equation, instead of introducing these variables all together, each one
was introduced separately. If it achieved statistical significance, it was maintained while
the next variable was introduced and if not, it was dropped.
A quick inspection of the seven tables reveals that only two arts-related predictors
achieved statistical significance in a final regression equation and only in the regression
involving General Health. As well, only one demographic variable achieved statistical
significance in a final equation and that was also in the regression involving General Health.
This was somewhat similar to the regression results reported in Michalos and Kahlke
(2008). In the latter study only the Indexes of Arts as Self-Health Enhancers and Spirit-
Building (not used in this study) achieved statistical significance in the final equation of one
Table 15 Correlations among motivational indexes and seven life assessment variables
Index GH Lsat hap qolsat SWLS CLAS SWB
Health .21 ns .10 .08 .08 ns ns
S-Dev .17 ns .08 ns ns ns ns
Comb .24 .14 .09 .14 .13 ns .13
Ends .17 .09 ns ns ns ns ns
NC614; P\0.05
24 A. C. Michalos, P. M. Kahlke
123
life assessment variable, namely, satisfaction with the overall quality of life (qolsat). In that
study, on five occasions some demographic variable achieved statistical significance.
The first column of figures in Table 16 shows that two of our four demographic pre-
dictors remained statistically significant when pressed into service together and that col-
lectively they explained 8.0% of the variation in self-reported General Health (GH) scores.
The most influential was education, with a Beta value of b=.25, followed by the Body
Mass Index at b=-0.14. Thus, figuratively speaking, for example, one could say that on
average, for every increase of a full unit step (i.e., one standard deviation unit) of edu-
cation, respondents got an increase of 25.0% of a step in self-reported General Health, with
the values of all other predictors held constant. The second column of figures shows that
when the four motivational indexes were used together as predictors, two remained sta-
tistically significant and they explained 7.0% of the variance in General Health scores. The
Index of Arts as Community Builders (Comb) was most influential, with a Beta value of
b=.19. The third column of figures shows that two arts-related variables from the hours
per week set of predictors remained statistically significant and explained 4.0% of the
variance in General Health scores, with the mean level of satisfaction obtained from
watching dvd films having the most influence at b=-0.17. The fourth column of figures
shows that two of the domain satisfaction predictors remained statistically significant and
together they explained 17.0% of the variance in General Health scores. (Because the
dependent variable for this table is self-reported General Health and such reports are highly
correlated with satisfaction with one’s own health (Michalos 2004), the latter variable was
not used as a predictor of General Health.) Reported satisfaction with respondents’ rec-
reational activities was most influential, with a b=.33, followed by satisfaction with
respondents’ own self-esteem, b=.15. In the final column, we see that five predictors
combined to explain 20.0% of the variance in General Health scores (N=241), with
satisfaction with respondents’ recreation activity appearing most influential (b=.25),
followed by self-esteem satisfaction (b=.19). Two arts-related predictors remained sta-
tistically significant in the last regression. The Index of Arts as Community Builders
(Comb) had a b=.14 and the average number of hours per week spent watching dvd films
had a b=-0.13. In Michalos and Kahlke (2008) we were able to explain 32.0% of the
variance in GH scores, with satisfaction with respondents’ recreational activities most
influential, (b=.28).
Table 16 Regressions of General Health on demographics, motivation indexes, hours/times engaged and
satisfaction obtained from arts-related activities and domain satisfaction
Dependent variables Demog. Mot.Index Hours/act.sat. Domain sat. All Pred
N507 596 199 678 241
% of variance expl 8 7 4 17 20
Predictors bb b b b
Education .25 * * * **
Body Mass Index -.14 * * * -.13
Comm. Building Ind * .19 * * .14
Health enhance Ind. * .10 * * **
Watching films dvd * * -.17 * -.13
Reading novels sat. * * .14 * **
Recreat act. sat. * * * .33 .25
Self-Esteem sat. * * * .15 .19
* Not in equation, ** significance level too low to enter equation
Arts and the Perceived Quality of Life in British Columbia 25
123
The first column of figures in Table 17 shows that only one of our four demographic
predictors remained statistically significant and it explained 1.0% of the variation in sat-
isfaction with life as a whole (Lsat) scores. Household income had a Beta value of b=.09.
The second column of figures shows that one of the 4 motivational indexes remained
statistically significant when the 4 were used together and that by itself that one explained
only 2.0% of the variance in life satisfaction scores, with the Index of Arts as Community
Builders (Comb) having a Beta value of b=.15. The third column of figures shows that
one arts-related variable from the hours per week set of predictors remained statistically
significant and explained 3.0% of the variance in life satisfaction (Lsat) scores. Respon-
dents’ mean levels of satisfaction obtained from reading novels, etc. had a b=.18. The
fourth column of figures shows that two arts-related variables from the times per year set of
predictors remained statistically significant. Satisfaction obtained from going to concerts
and non-art museums each had a b=.16, and together explained 7.0% of the variance in
life satisfaction scores. The fifth column of figures shows that six of the domain satisfaction
predictors remained statistically significant and together they explained 66.0% of the
variance in life satisfaction scores. The most influential explanatory variable was satis-
faction with one’s own health (b=.25), followed by satisfaction with respondents’
friendships (b=.21). The final column shows that the addition of each of the demographic
and arts-related predictors (one at a time with replacement) to the six significant domain
satisfaction predictors from the fifth column produced no change in our explanatory power.
All the figures in columns five and six are the same, but the 5 double asterisks in the sixth
column mean that in the presence of the 6 domain satisfaction predictors, no explanatory
power was added by the demographic and arts-related predictors. In our earlier study, we
were able to explain 71.0% of the variance in Lsat scores, with satisfaction with one’s own
health again most influential, (b=.24).
The first column of figures in Table 18 shows that one demographic predictor remained
statistically significant and it explained 1.0% of the variation in happiness (Hap) scores.
Household income had a b=.12. The second column of figures shows that when the four
Table 17 Regressions of life satisfaction on demographics, motivation indexes, hours/times engaged and
satisfaction obtained from arts-related activities and domain satisfaction
Dependent variables Demog. Mot. Index Hours/act.sat. Times/sat. Domain sat. All Pred
N500 593 430 223 550 550
% of varience expl 1 2 3 7 66 66
Predictors bb b b b b
Household income .09 * * * * **
Comm. Building Ind * .15 * * * **
Reading novels sat. * * .18 * * **
Go other museums sat. * * * .16 * **
Go concert sat. * * * .16 * **
Future security sat. * * * * .10 .10
Job sat. * * * * .20 .20
Friendship sat * * * * .21 .21
Health satisfaction * * * * .25 .25
Sense/mean life sat. * * * * .16 .16
Self-esteem sat. * * * * .15 .15
* Not in equation, ** significance level too low to enter equation
26 A. C. Michalos, P. M. Kahlke
123
motivational indexes were used together as predictors, only one remained statistically
significant and by itself explained 1.0% of the variance in happiness scores. The Index of
Arts as Self-Health Enhancers had a b=.11. The third column of figures shows that a
single arts-related variable from the hours per week set of predictors remained statistically
significant and it explained 2.0% of the variance in happiness scores, with the mean level
of satisfaction obtained from singing alone having a b=.15. (Notice, then, that while the
average number of hours per week invested in singing alone decreased respondents’ sat-
isfaction with life as a whole (Table 8), the mean level of satisfaction obtained from
singing alone increased their happiness Tables 8and 18). The fourth column of figures
shows that one arts-related variable from the times per year set of predictors remained
statistically significant. The satisfaction obtained from going to art museums (b=.19)
explained 3.0% of the variance in happiness scores. The fifth column of figures shows that
5 of the domain satisfaction variables remained statistically significant and explained
45.0% of the variance in happiness scores. The most influential explanatory variable was
satisfaction with respondents’ own self-esteem, b=.35, followed by satisfaction with
their future security, b=.18. Again, the final column shows that the addition of each of
the demographic and arts-related predictors (one at a time with replacement) to the 5
significant domain satisfaction predictors from the fifth column produced no change in our
explanatory power. In our earlier study, we were able to explain 51.0% of the variance in
Hap scores, with satisfaction with one’s own health most influential, b=.33.
The first column of figures in Table 19 shows that one of our four demographic vari-
ables remained statistically significant and explained 2.0% of the variation in satisfaction
with the overall quality of life (qolsat) scores. Household income had a b=.16. The
second column of figures shows that one of the four motivational indexes remained sta-
tistically significant and explained 2.0% of the variance in satisfaction with the overall
quality of life scores, i.e., the Index of Arts as Community Builders, b=.14. The third
column of figures shows that a single arts-related variable from the hours per week set of
predictors remained statistically significant, satisfaction obtained from singing alone,
b=.13, and it explained 1.0% of the variance in satisfaction with the overall quality of
life scores. The fourth column of figures shows that a single arts-related variable from the
Table 18 Regressions of happiness on demographics, motivation indexes, hours/times engaged and sat-
isfaction obtained from arts-related activities and domain satisfaction
Dependent variables Demog. Mot. Index Hours/act.sat Times/sat. Domain sat. All Pred
N505 595 235 378 669 669
% of variance expl 1 1 2 3 45 45
Predictors bb b b b b
Household income .12 * * * * **
Health enhance Ind. * .11 * * * **
Singing alone sat. * * .15 * * **
Go art museum sat. * * * .19 * **
Future security sat. * * * * .18 .18
Recreation act. sat. * * * * .10 .10
Friendships sat. * * * * .10 .10
Health sat. * * * * .10 .10
Self-esteem sat. * * * * .35 .35
* Not in equation, ** significance level too low to enter equation
Arts and the Perceived Quality of Life in British Columbia 27
123
times per year set of predictors remained statistically significant, satisfaction obtained from
going to historical sites, b=.19, and it explained 3.0% of the variance in satisfaction with
the overall quality of life scores. The fifth column of figures shows that 7 of the domain
satisfaction predictors remained statistically significant and together they explained 60.0%
of the variance in satisfaction with the overall quality of life scores. The most influential
explanatory variables were satisfaction with respondents’ treatment by local residents,
b=.22, followed by satisfaction with respondents’ health, b=.19. Again, the final
column shows that the addition of each of the demographic and arts-related predictors to
the 7 significant domain satisfaction predictors from the fifth column produced no change
in our explanatory power. In our earlier study, we were able to explain 63.0% of the
variance in qolsat scores, with satisfaction with respondents’ health, financial security and
sense of meaning in life most influential, each b=.16.
The first column of figures in Table 20 shows that 3 of 4 demographic variables
remained statistically significant and collectively explained 4.0% of the variation in scores
on the 5-item Satisfaction With Life Scale (SWLS). Of the three predictors, the most
influential were household income and education, each b=.12. The second column of
figures shows that only one of the 4 motivational indexes remained statistically significant
and that explained 2.0% of the variance in SWLS scores. The Index of Arts as Community
Builders (Comb) had a b=.14. The third column of figures shows that a single arts-related
variable from the times per year set of predictors remained statistically significant, satis-
faction obtained from going to non-art museums, b=.21, and it explained 4.0% of the
variance in SWLS scores. The fourth column of figures shows that 6 of the domain
satisfaction predictors remained statistically significant and together they explained 51.0%
of the variance in SWLS scores. The most influential explanatory variables were satis-
faction with respondents’ sense of meaning in life and self-esteem, each b=.21, followed
by satisfaction with respondents’ health, b=.17. Again, the final column shows that the
addition of each of the demographic and arts-related predictors to the 6 significant domain
Table 19 Regressions of satisfaction with the overall quality of life on demographics, motivation indexes,
hours/times engaged and satisfaction obtained from arts-related activities and domain satisfaction
Dependent variables Demog. Mot. Index Hours/act.sat. Times/sat. Domain sat. All Pred
N504 596 236 361 664 664
% of variance expl 2 2 1 3 60 60
Predictors bb b b b b
Household income .16 * * * * **
Comm. Building Ind * .14 * * * **
Singing alone sat. * * .13 * * **
Go historic sites sat. * * * .19 * **
Local treatment sat. * * * * .22 .22
Health satisfaction * * * * .19 .19
Finance security sat. * * * * .09 .09
Future security sat. * * * * .15 .15
Sense meaning sat. * * * * .14 .14
Recreation sat. * * * * .17 .17
Feel part comm sat. * * * * .07 .07
* Not in equation, ** significance level too low to enter equation
28 A. C. Michalos, P. M. Kahlke
123
satisfaction predictors from the fourth column produced no change in our explanatory
power. In our earlier study, we were able to explain 48.0% of the variance in SWLS scores,
with satisfaction with one’s financial security most influential, b=.22.
The first column of figures in Table 21 shows that two demographic variables remained
statistically significant and explained 3.0% of the variation in scores on the 5-item Con-
tentment with Life Assessment Scale (CLAS). Of the two predictors, the most influential
was household income, b=.13. The second column of figures shows that a single arts-
related variable from the times per year set of predictors remained statistically significant,
satisfaction obtained from visiting historic and heritage sites, b=.15, and explained 2.0%
Table 21 Regressions of contentment with life assessment Scale (CLAS) on demographics, motivation
indexes, hours/times engaged and satisfaction obtained from arts-related activities and domain satisfaction
Dependent variables Demog. Times/sat. Domain sat. All Pred
N493 353 538 538
% of variance expl 3 2 50 50
Predictors bb b b
Age .12 * * **
Household income .13 * * **
Singing alone sat. * * * **
Go historic site sat. * .15 * **
Job satisfaction * * .12 .12
Health satisfaction * * .10 .10
Self-esteem sat. * * .26 .26
Future security sat. * * .18 .18
Sense meaning sat. * * .16 .16
Recreation act sat. * * .09 .09
* Not in equation, ** significance level too low to enter equation
Table 20 Regressions of satisfaction with life scale (SWLS) on demographics, motivation indexes, hours/
times engaged and satisfaction obtained from arts-related activities and domain satisfaction
Dependent variables Demog. Mot. Index Times/sat. Domain sat. All Pred
N487 582 308 534 534
% of variance expl 4 2 4 51 51
Predictors bb b b b
Household income .12 * * * **
Education .12 * * * **
Age .11 * * * **
Comm. Building Ind * .14 * * **
Go other museums sat. * * .21 * **
Sense meaning sat. * * * .21 .21
Job sat. * * * .09 .09
Health satisfaction * * * .17 .17
Finance security sat. * * * .15 .15
Feel part comm sat. * * * .09 .09
Self-esteem sat. * * * .21 .21
* Not in equation, ** significance level too low to enter equation
Arts and the Perceived Quality of Life in British Columbia 29
123
of the variance in CLAS scores. The third column of figures shows that 6 of the domain
satisfaction variables remained statistically significant and together explained 50.0% of the
variance in CLAS scores. The most influential explanatory variables were satisfaction with
respondents’ self-esteem, b=.26, followed by satisfaction with respondents’ future
security, b=.18. Again, the final column shows that the addition of each of the demo-
graphic and arts-related predictors to the 6 significant domain satisfaction predictors from
the third column produced no change in our explanatory power. In our earlier study, we
were able to explain 71.0% of the variance in CLAS scores, with satisfaction with
respondents’ financial security most influential, b=.19.
The first column of figures in Table 22 shows that two demographic variables remained
statistically significant and explained 4.0% of the variation in scores on the 4-item Sub-
jective Wellbeing Index (SWB). Of the two predictors, the most influential was household
income, b=.17. The second column of figures shows that one of the 4 motivational
indexes remained statistically significant and explained 2.0% of the variance in SWB
scores. The Index of Arts as Community Builders had a b=.14. The third column of
figures shows that a single arts-related variable from the hours per week set of predictors
remained statistically significant, satisfaction obtained from reading novels, etc., b=.15,
and explained 2.0% of the variance in SWB scores. The fourth column of figures shows
that one arts-related variable from the times per year set of predictors remained statistically
significant and explained 3.0% of the variance in SWB scores. Satisfaction obtained from
going to art museums had a b=.17. The fifth column of figures shows that 9 of the
domain satisfaction predictors remained statistically significant and together explained
75.0% of the variance in SWB scores. The most influential explanatory variables were
satisfaction with respondents’ financial security, b=.20, followed by satisfaction with
respondents’ health, b=.19. Again, the final column shows that the addition of each of
Table 22 Regressions of Subjective Wellbeing (SWB) on demographics, motivation indexes, hours/times
engaged and satisfaction obtained from arts-related activities and domain satisfaction
Dependent variables Demog. Mot. Index Hours/act.sat. Times/sat. Domain sat. All Pred
N491 583 423 374 644 644
% of variance expl 4 2 2 3 75 75
Predictors bb b b b b
Education .10 * * * * **
Household income .17 * * * * **
Comm. Building Ind. * .14 * * * **
Reading novels sat. * * .15 * * **
Go art museum sat. * * * .17 * **
Local treatment sat. * * * * .10 .10
Friendships sat. * * * * .11 .11
Future security sat. * * * * .13 .13
Health satisfaction * * * * .19 .19
Finance security sat. * * * * .20 .20
Sense meaning sat * * * * .12 .12
Self-esteem sat. * * * * .14 .14
Recreation act sat. * * * * .12 .12
Feel part comm sat. * * * * .06 .06
* Not in equation, ** significance level too low to enter equation
30 A. C. Michalos, P. M. Kahlke
123
the demographic and arts-related predictors to the 9 significant domain satisfaction pre-
dictors from the fifth column produced no change in our explanatory power. In our earlier
study, we were able to explain 79.0% of the variance in SWB scores, with satisfaction with
respondents’ financial security most influential, b=.25.
Table 23 lists results of regressing our 7 life assessment variables on 7 mean respon-
dent-calculated discrepancy scores. Although the predictors are drawn from multiple
discrepancies theory (MDT), the whole theory is not applied here. All we have done is use
the 7 basic discrepancy variables of MDT in a simple bottom-up type of linear regression
of the sort applied to produce Exhibits 16–22. On average, the 7 MDT variables explained
44.0% (vs. 48.0% in the earlier study) of the variation in life assessment scores, with a high
of 59.0% for SWLS and a low of 16.0% for GH. Without GH, the average variance
explained was 49.0%. The difference between the power of the MDT variables to explain
General Health versus the other 6 life assessment variables (replicating results in our
earlier study) suggests again that respondents recognized a difference between a healthy
life and a good life, all things considered. Setting aside the GH column, in every column,
the most influential variable is that indicating the perceived discrepancy between what
respondents have now and what they want. On average, the Beta value for this variable is
b=.42, with a high of b=.46 for SWB and a low of b=.34 for qolsat. The only other
MDT predictor with a significant association with each of the 7 life assessment variables in
the presence of all other MDT predictors is that for the gap between what respondents have
now and the best they ever had in the past. On average, this predictor had a b=.18.
Since in every case of Tables 16–22, the set of domain satisfaction predictors explained
the greatest amount of variance in our life assessment variables, the column headed
‘Domain sat.’ in these tables is the appropriate column to compare with the results in
Table 23 in order to assess the relative explanatory power of both sets of predictors, i.e.,
domain satisfaction versus discrepancy predictors. On average for the 7 life assessment
variables, domain satisfaction predictors clearly explained a greater percent of the variance
than discrepancy predictors, 52.0 versus 44.0% (compared to 57 and 48% in the earlier
study). This is not particularly surprising or satisfying since, after all, in the former case
one is using only domain satisfaction predictors to explain some sort of a more general
level of satisfaction. Much more analysis will be required to make a comprehensive
comparison of the relative power of MDT versus a simple domain satisfaction, bottom-up
approach to explaining the variation of overall life assessment scores in the context of a
plausible theory that includes arts-related variables.
Table 23 Regressions of seven life assessment variables on seven mean discrepancy scores
Dependent variables GH Lsat hap qolsat SWLS CLAS SWB
N657 656 657 656 641 636 645
% of variance explained 16 39 43 43 59 51 58
Predictors, your life compared to bbbb b b b
What you want from life .17 .42 .43 .34 .43 .41 .46
What others your age & sex have .18 .12 .08 .21 .15 * .17
What you deserve -.12 * * * .08 .09 .09
What you need * * * .11 .10 .08 .09
What you expected it to be now * * .11 * * .19 .10
What you expect it to be in 5 years * * * * * * *
The best in your past experience .23 .22 .18 .15 .20 .13 .13
* Significance level too low to enter equation
Arts and the Perceived Quality of Life in British Columbia 31
123
7 Conclusion
The aims of this investigation were (1) to measure the impact of arts-related activities on
the perceived quality of life of a representative sample of British Columbians aged
18 years or more in the spring of 2007, and (2) to compare the findings of this study with
those of a sample of 1,027 adults drawn from 5 B.C. communities (Comox Valley,
Kamloops, Nanaimo, Port Moody and Prince George) in the fall of 2006. In May and June
2007, 708 British Columbians responded to a 13-page mailed out questionnaire. The
working data set was weighted by age and education to match the 2006 census statistics for
the province, yielding a fairly representative sample.
Since we were aiming to get some baseline provincial figures as well as to replicate
findings obtained from specifically targeted communities in different parts of the province,
the best way to summarize our results is with a double column review. This is provided in
Table 24. In broad strokes, out of 37 pairs of entries in this table, there are 10 (27.0%) in
which the province-wide and five-communities results are the same. There are another 13
Table 24 Comparisons between province-wide (2007, N=708) and five-communities (2006, N=1,027)
results
Province-wide sample Five-communities sample
Top 5 arts-related hours per week activities: listening
to music; reading novels, short stories, plays or
poetry; watching films on dvd; singing alone;
reading to others
Same
Top 5 arts-related hours per week activities: average
hours per week engaged =6.9
7.0
Top 5 arts-related hours per week activities: average
levels of satisfaction =5.9
Same
Top 5 arts-related times per year activities: go to
movies, concerts, community festivals, historic
sites, art museums
Same
Top 5 arts-related times per year activities: average
times per year going =3.8
3.9
Top 5 arts-related times per year activities: average
levels of satisfaction =5.8
Same
First thoughts about ‘arts’ =painting, drawing Same
Most important arts =music Same
Place where first learned about arts =school Same
Mean age when first learned =12 12.7
Mean level of satisfaction with access to activity,
information, place, access to place, price =5.1
5.3
Mean level of satisfaction with support from city,
provincial, federal government and others =4.0
Same
Index of arts as self-health enhancers a=.87 .88
Index of arts as self-developing activities a=.86 .89
Index of arts as community builders a=.82 .86
Index of arts as ends in themselves a=.71 .77
Satisfaction with life scale (SWLS) a=.90 .89
Contentment with life assessment scale (CLAS)
a=.87
.86
32 A. C. Michalos, P. M. Kahlke
123
Table 24 continued
Province-wide sample Five-communities sample
Subjective wellbeing index (SWB) a=.87 .88
Average level of satisfaction on 30 domain/aspect
items =5.3
5.4
Average level of satisfaction with life as a whole,
standard of living, quality of life and
happiness =5.8
Same
Top 2 discrepancy items =have/want, have/others
have
Same
Demographic variable with highest average
correlation with 7 life assessment variables =
household income, r=0.12
r=0.20
Hours per week arts-related variables with highest
and second highest average correlations with 7 life
assessment variables: satisfaction obtained from
arranging flowers, r=0.25; satisfaction obtained
from taking kids to arts-related activities, r=
-0.17
Satisfaction obtained from playing a
musical instrument, r=0.25; satisfaction
obtained from singing in a group, r=0.17
Life assessment variable with largest number of
significant associations with hours per week arts-
related variables: satisfaction with the overall
quality of life tied with happiness
Satisfaction with the overall quality of life
Times per year arts-related variables with highest
and second highest average correlations with 7 life
assessment variables: satisfaction obtained from
going to amateur theatre performances, r=0.27;
satisfaction obtained from going to professional
theatre performances, r=0.22
Satisfaction obtained from going to non-art
museums, r=0.14; satisfaction obtained from
going to amateur theatre performances, r=0.13
Life assessment variable with largest number of
significant associations with times per year arts-
related variables: satisfaction with the overall
quality of life
General health
Domain/aspect satisfaction items with highest and
second highest average correlations with 7 life
assessment variables: satisfaction with one’s own
health, r=0.60; satisfaction with one’s self-
esteem, r=0.59
Satisfaction with one’s own health, r=0.64;
satisfaction with one’s self-esteem, r=0.57
Percent of variation explained in general health
scores by all predictors =20.0%, with most
influential predictor =respondents’ satisfaction
with their recreation activities, b=.25
Percent of variation explained in general health
scores by all predictors =32.0%, with most
influential predictor =respondents’ satisfaction
with their recreation activities, b=.28
Percent of variation explained in satisfaction with
life as a whole scores (Lsat) by all
predictors =66.0%, with most influential
predictor =respondents’ satisfaction with their
own health, b=.25
Percent of variation explained in satisfaction with
life as a whole scores (Lsat) by all
predictors =71.0%, with most influential
predictor =respondents’ satisfaction with their
own health, b=.24
Percent of variation explained in happiness scores by
all predictors =45.0%, with most influential
predictor =respondents’ satisfaction with their
own self-esteem, b=.35
Percent of variation explained in happiness scores
by all predictors =51.0%, with most influential
predictor =respondents’ satisfaction with their
own health, b=.33
Arts and the Perceived Quality of Life in British Columbia 33
123
(35.0%) in which the results are very nearly the same. So, we have a total of 23 (62.0%)
pairs with considerable similarity. While plenty of differences were identified in many of
the tables in our main text, suggesting that there remains a great deal of diversity yet to be
understood, the broad similarities seem to be quite remarkable.
In the light of results from our two samples and in the context of all our predictors,
based on the relative impact of all the arts-related activities and the satisfaction obtained
from those activities on the seven overall life assessment variables, it is fair to say that such
activities and their corresponding satisfaction contributed relatively little. As remarked in
our earlier study, it is important to keep in mind the initial condition, ‘‘in the context of all
our predictors’’ and the qualifier ‘‘relatively’’. In that context, even the usually powerful
explanatory variables concerning interpersonal relations (i.e., satisfaction with one’s living
partner, family and friendships) had very little impact. Of the three, only satisfaction with
one’s friendships appeared in any final regression equation for the provincial sample and
only for Lsat, Hap and SWB. This was quite different from the five-communities sample.
In the latter, satisfaction with one’s living partner appeared in the final equations for 6 of
the 7 dependent variables (excluding General Health), satisfaction with family relations
appeared in the final equations for Lsat and Hap, and satisfaction with friendships appeared
in the final equations for Lsat, qolsat and SWB.
Considering domain/aspect predictors, what did most of the explanatory work for the 7
life assessment variables? Two samples with 7 final regression equations and no ties would
Table 24 continued
Province-wide sample Five-communities sample
Percent of variation explained in satisfaction with the
overall quality of life scores (qolsat) by all
predictors =60.0%, with most influential
predictor =respondents’ satisfaction with their
treatment by local residents, b=.22
Percent of variation explained in satisfaction with
the overall quality of life scores (qolsat) by all
predictors =63.0%, with most influential
predictors =respondents’ satisfaction with their
own health, financial security and sense of
meaning in life, each b=.19
Percent of variation explained in satisfaction with
life scale scores (SWLS) by all
predictors =51.0%, with most influential
predictor =respondents’ satisfaction with their
own self-esteem and sense of meaning in life,
b=.21
Percent of variation explained in satisfaction with
life scale scores (SWLS) by all
predictors =48.0%, with most influential
predictor =respondents’ satisfaction with their
financial security, b=.22
Percent of variation explained in contentment with
life assessment scale scores (CLAS) by all
predictors =50.0%, with most influential
predictor =respondents’ satisfaction with their
own self-esteem, b=.26
Percent of variation explained in contentment with
life assessment scale scores (CLAS) by all
predictors =71.0%, with most influential
predictor =respondents’ satisfaction with their
financial security, b=.19
Percent of variation explained in subjective
wellbeing index scores (SWB) by all
predictors =75.0%, with most influential
predictor =respondents’ satisfaction with their
financial security, b=.20
Percent of variation explained in subjective
wellbeing index scores (SWB) by all
predictors =79.0%, with most influential
predictor =respondents’ satisfaction with their
financial security, b=.25
Average percent of variation explained in 7 life
assessment variables by all domain/aspect
predictors =52.0%
Average percent of variation explained in 7 life
assessment variables by all domain/aspect
predictors =57.0%
Average percent of variation explained in 7 life
assessment variables by 7 MDT
predictors =44.0%
Average percent of variation explained in 7 life
assessment variables by 7 MDT
predictors =48.0%
34 A. C. Michalos, P. M. Kahlke
123
have given us 14 possible most influential predictors. Since we had one regression with a
3-way tie for most influential predictor and one with a 2-way tie, we have 17 entries. One
way to answer our question is to count the relative frequency with which various predictors
occur. Using this crude measure, one finds that satisfaction with financial security had 5
firsts, followed by 4 firsts for satisfaction with respondents’ own health and 3 firsts for
satisfaction with respondents’ own self-esteem. These predictors are understandably and
often relatively heavy hitters in such exercises. Still, granting the difficulties of displacing
any of the relatively heavy hitters from our final explanatory equations, it remains unclear
why even arts-related activities with engagement measured in the average number of hours
per week or times per year and the satisfaction obtained from such engagement were
relatively weak predictors in the context of only such arts-related activities and satisfac-
tion. Hopefully, others will be able to solve this problem in the future.
Acknowledgments We would like to express our thanks to the Social Sciences and Humanities Research
Council for funding this research through the Gold Medal for Achievement in Research 2004. This project
complements an earlier one also funded by the Council through its Community-University Research grants
program, with Will Garrett-Petts of Thompson Rivers University Principal Investigator. We would also like
to thank Joyce Henley, Office Manager of ISRE, and all the anonymous respondents who shared their time
and thoughts with us to make this report possible.
Appendix: BC Arts and Quality of Life Survey, May 2007
See Table 25
Table 25 Time spent on and levels of satisfaction with artistic activities (Total N=708, unweighted data)
Ordered by
Particular activities N Hours/Week Satisfaction
T1. Listening to music 608 13.22 6.01
T17. Reading novels, etc. 441 7.67 6.17
T37. Watching movies on video 278 4.96 5.60
T8. Singing alone 239 4.58 5.70
T21. Reading to others 195 3.27 6.03
T46. Gourmet cooking 136 4.60 6.18
T20. Telling stories 122 2.76 5.92
T5. Painting or drawing 118 5.86 5.97
T9. Singing in a group 103 2.67 6.11
T50. Watching art shows on TV 94 2.68 5.66
T2. Playing a musical instrument 85 4.91 6.05
T40. Artistic photography 66 3.11 6.34
T27. Knitting or crocheting 64 4.98 6.45
T42. Arranging flowers 57 1.37 6.38
T67. Other 50 10.00 6.65
T52. Watching concerts on TV 48 2.17 5.93
T12. Taking children to arts activities 46 2.35 5.96
T19. Writing novels, etc. 45 6.18 5.89
T28. Embroidery, needlepoint 38 5.95 6.31
T16. Making quilts 32 9.75 6.29
Arts and the Perceived Quality of Life in British Columbia 35
123
Table 25 continued
Ordered by
Particular activities N Hours/Week Satisfaction
T15. Making clothes 30 4.27 6.07
T6. Teaching painting or drawing 23 5.13 6.05
T51. Watching live theatre on TV 23 2.48 5.42
T7. Teaching singing 21 3.90 6.05
T56. Attending a class-artistic work 20 3.65 6.39
T14. Designing clothes 17 2.47 5.94
T49. Graphic designing 17 16.29 5.63
T4. Teaching—to play an instrument 15 4.27 5.20
T24. Teaching people to dance 14 2.29 5.85
T43. Creating jewelry 14 2.64 5.56
T11. Creating sculptures 13 5.38 6.30
T47. Teaching gourmet cooking 13 2.85 6.30
T53. Watching opera on TV 12 3.17 5.38
T10. Creating pottery or ceramics 11 7.00 5.78
T18. Attending a book club 11 4.45 6.00
T60. Working for pay in the arts 10 26.80 6.22
T22. Teaching creative writing 9 2.33 5.63
T3. Writing music 7 4.43 5.57
T62. Acting as an advocate for the arts 7 1.71 6.33
T58. Selling works of art 6 2.33 5.83
T25. Weaving textiles 4 13.75 6.67
T35. Non-acting work—amateur theatre 2 2.50 6.50
T26. Weaving baskets 1 4.00 7.00
T34. Acting—amateur theatre 1 6.00 –
T48. Making artistic videos or movies 1 10.00 7.00
T61. Serving as a judge for the arts 1 2.00 –
T33. Acting—professional theatre 0
T13. Teaching sculpture 0
Ordered by
Particular activities N Times/Year Satisfaction
T36. Going to movies 439 5.97 5.53
T29. Going to concerts 417 3.75 6.01
T38. Going to art museums/galleries 384 3.65 5.84
T65. Visiting historic, heritage sites 367 2.97 5.93
T54. Attending community festivals 365 2.89 5.61
T39. Going to other museums 319 2.39 5.84
T66. Visiting the public library 307 9.18 5.61
T30. Going to amateur live theatre 296 2.56 5.90
T31. Going to professional live theatre 293 2.80 6.14
T57. Buying works of art 224 2.33 6.12
T44. Decorating a home 220 6.08 5.75
T32. Going to school plays 211 2.13 6.00
36 A. C. Michalos, P. M. Kahlke
123
Table 25 continued
Ordered by
Particular activities N Times/Year Satisfaction
T23. Dancing 199 5.48 5.52
T41. Designing a garden 190 4.19 6.07
T63. Making donations to the arts 111 2.62 5.79
T55. Working on community festivals 98 2.43 5.77
T59. Volunteering in the arts 53 4.94 5.94
T64. Designing, crafting furniture 49 4.16 6.02
T45. Figure skating 32 5.22 5.50
T67. Other 25 9.52 6.48
T61. Serving as a judge for the arts 8 3.00 6.14
T33. Acting—professional theatre 7 2.00 6.14
T34. Acting—amateur theatre 6 1.67 6.50
Ordered by
Particular activities N Hours/Week Satisfaction
T60. Working for pay in the arts 10 26.80 6.22
T49. Graphic designing 17 16.29 5.63
T25. Weaving textiles 4 13.75 6.67
T1. Listening to music 608 13.22 6.01
T67. Other 50 10.00 6.65
T48. Making artistic videos or movies 1 10.00 7.00
T16. Making quilts 32 9.75 6.29
T17. Reading novels, etc. 441 7.67 6.17
T10. Creating pottery or ceramics 11 7.00 5.78
T19. Writing novels, etc. 45 6.18 5.89
T34. Acting—amateur theatre 1 6.00 –
T28. Embroidery, needlepoint 38 5.95 6.31
T5. Painting or drawing 118 5.86 5.97
T11. Creating sculptures 13 5.38 6.30
T6. Teaching painting or drawing 23 5.13 6.05
T27. Knitting or crocheting 64 4.98 6.45
T37. Watching movies on video 278 4.96 5.60
T2. Playing a musical instrument 85 4.91 6.05
T46. Gourmet cooking 136 4.60 6.18
T8. Singing alone 239 4.58 5.70
T18. Attending a book club 11 4.45 6.00
T3. Writing music 7 4.43 5.57
T4. Teaching—to play an instrument 15 4.27 5.20
T15. Making clothes 30 4.27 6.07
T26. Weaving baskets 1 4.00 7.00
T7. Teaching singing 21 3.90 6.05
T56. Attending a class-artistic work 20 3.65 6.39
T21. Reading to others 195 3.27 6.03
T53. Watching opera on TV 12 3.17 5.38
Arts and the Perceived Quality of Life in British Columbia 37
123
Table 25 continued
Ordered by
Particular activities N Hours/Week Satisfaction
T40. Artistic photography 66 3.11 6.34
T47. Teaching gourmet cooking 13 2.85 6.30
T20. Telling stories 122 2.76 5.92
T50. Watching art shows on TV 94 2.68 5.66
T9. Singing in a group 103 2.67 6.11
T43. Creating jewelry 14 2.64 5.56
T35. Non-acting work—amateur theatre 2 2.50 6.50
T51. Watching live theatre on TV 23 2.48 5.42
T14. Designing clothes 17 2.47 5.94
T12. Taking children to arts activities 46 2.35 5.96
T22. Teaching creative writing 9 2.33 5.63
T58. Selling works of art 6 2.33 5.83
T24. Teaching people to dance 14 2.29 5.85
T52. Watching concerts on TV 48 2.17 5.93
T61. Serving as a judge for the arts 1 2.00 –
T62. Acting as an advocate for the arts 7 1.71 6.33
T42. Arranging flowers 57 1.37 6.38
T33. Acting—professional theatre 0
T13. Teaching sculpture 0
Ordered by
Particular activities N Times/Year Satisfaction
T67. Other 25 9.52 6.48
T66. Visiting the public library 307 9.18 5.61
T44. Decorating a home 220 6.08 5.75
T36. Going to movies 439 5.97 5.53
T23. Dancing 199 5.48 5.52
T45. Figure skating 32 5.22 5.50
T59. Volunteering in the arts 53 4.94 5.94
T41. Designing a garden 190 4.19 6.07
T64. Designing, crafting furniture 49 4.16 6.02
T29. Going to concerts 417 3.75 6.01
T38. Going to art museums/galleries 384 3.65 5.84
T61. Serving as a judge for the arts 8 3.00 6.14
T65. Visiting historic, heritage sites 367 2.97 5.93
T54. Attending community festivals 365 2.89 5.61
T31. Going to professional live theatre 293 2.80 6.14
T63. Making donations to the arts 111 2.62 5.79
T30. Going to amateur live theatre 296 2.56 5.90
T55. Working on community festivals 98 2.43 5.77
T39. Going to other museums 319 2.39 5.84
T57. Buying works of art 224 2.33 6.12
T32. Going to school plays 211 2.13 6.00
38 A. C. Michalos, P. M. Kahlke
123
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Table 25 continued
Ordered by
Particular activities N Times/Year Satisfaction
T33. Acting—professional theatre 7 2.00 6.14
T34. Acting—amateur theatre 6 1.67 6.50
Most activities had some people indicating they spent a certain number of hours per week on it, while other
people only did it a few times per year. The hours per week activities are listed first, followed by the times
per year activities. The activities are listed in two orders—first from the largest number of people responding
to the least and then from the largest average hours/week (or times/year) to the smallest
Arts and the Perceived Quality of Life in British Columbia 39
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